Dpuiu HTS

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Summary

 Vendor:                       Roche                   Illumina                          ABI             
 Technology:                   454                     Solexa GA                        SOLiD
                       --------------------    --------------------------------     ------------------      
 Platform:             GS20    FLX     Ti      I       II      IIx     HiSeq200     1       2       3
 Reads: (M)            0.5     0.5     1.25    28      100     150                  40      115     320

 Fragment
 Read length:          100     200     400     35      50      100     100          25      35      50
 Insert: 0 (unmates)
 Run time: (d)         0.25    0.3     0.4     3       3       5       8            6       5       8
 Yield: (Gb)           0.05    0.1     0.5     1       5       15      200          1       4       16
 Rate: (Gb/d)          0.2     0.33    1.25    0.33    1.67    3       25           0.34    1.6     2
 Images: (TB)          0.01    0.01    0.03    0.5     1.1     2.8                  1.8     2.5     1.9
 PA Disk: (GB)         3       3       15      175     300     300                  300     750     1200
 PA CPU: (hr)          10      140     220     100     70      NA                   NA      NA      NA
 SRA: (GB)             0.5     1       4       30      50      2.5                  100     140     600

 Paired-end
 Read length:                  200     400     2×35    2×50    2×100                2×25    2×35    2×50
 Insert: (kb)                  3.5     3.5     0.2     0.2     0.2                  3       3       3
 Run time: (d)                 0.3     0.4     6       10      10                   12      10      16
 Yield: (Gb)                   0.1     0.5     2       9       30                   2       8       32
 Rate: (Gb/d)                  0.33    1.25    0.33    1.67    3                    0.34    1.6     2
 Images: (TB)                  0.01    0.03    1       2.2     5.6                  3.6     5       3.8
 PA Disk: (GB)                 3       15      350     500     500                  600     1500    2400
 PA CPU: (hr)                  140     220     160     120     NA                   NA      NA      NA
 SRA: (GB)                     1       4       60      100     3.5                  200     280     1200

 Mate-pair             
 Vendor:                       Roche                   Illumina                 ABI                  
 Technology:                   454                     Solexa GA               SOLiD                  
                       --------------------    --------------------    ------------------     
 Year                          2005                     2007                   2007                 
 Amplification             emulsion PCR               bridge PCR          emulsion PCR           
 Sequencing               pyrosequencing       sequencing-by-synthesis  ligase-based sequencing  
 ErrorsRate/bp                  5%                       1%                   <0.1% 
 DominantError         indels(esp homopolym)         substitutions          substitutions

Links

Modified Celera Assembler: the Celera Assembler software has modules for successive phases of assembly: pairwise overlap detection; initial ungapped multiple sequence alignments called unitigs; unitig consensus calculation; combination of unitigs with mate constraints to form contigs and scaffolds, which are ungapped and gapped multiple sequence alignments, respectively; and finally, scaffold consensus determination (Myers et al., 2000). Our approach to hybrid data assembly reuses the Celera Assembler scaffold and consensus modules. Independent of the hybrid problem, the scaffold module was revised to recover trimmed base calls confirmed by co-locating reads, and the consensus module was revised to determine alternate consensus sequences in regions of apparent polymorphism (Denisov et al., 2008). Our analysis narrowed the source of hybrid assembly problems to the overlap and unitig stages.

For speed, Celera Assembler relies on short exact matches between reads as seeds for overlap detection. Its exact-match algorithms were sensitive to the different proclivities for stutter observed between platforms. Stutter, that is, incorrect determination of the number of bases in homopolymer (single-letter) runs, is more prevalent in pyro reads than Sanger reads. We therefore modified the software to search for matches in compressed sequence, in which all single-letter repeats are reduced to a single base. The uncompressed sequence is consulted later before the seeds become overlaps.

Celera Assembler was sensitive to the different average read lengths between platforms. The shorter reads are more likely to be entirely contained within genomic repeats. Over-collapsed alignments of short repeat reads induce true and false overlaps to the interior of longer reads. Where the longer reads extend beyond the genomic repeats, they do not all overlap each other. The result is short reads with containment overlaps to multiple long reads that do not overlap each other. These overlap tangles were triggering Celera heuristics designed to detect mis-assembly, leading to unnecessarily short contigs.

Celera Assembler was also sensitive to the higher coverage typical of lower cost pyrosequencing. Higher coverage leads to increased collisions of reads with exactly the same prefix sequence. The assembler's arbitrary tie-breaking heuristics, sufficient for infrequent ties, had the potential to lead the assembler away from the global optimum in hybrid data. To address these problems we developed an aggressive approach to unitig construction that builds unitigs in greedy fashion, always following a read's best overlap (by an appropriate criterion), and ignoring contained reads at first. The aggressive unitigs initially incorporate mistakes that, ideally, are caught and corrected later by pattern analysis applied to best overlaps and mate constraints. High coverage could also increase the number of spurs, that is, reads with invalid sequence at one end. These seemed to contribute to fractured unitigs on hybrid data. We realized the software could turn higher coverage to its advantage by carefully trimming reads of unconfirmed sequence.'

De novo assemblers

Performance measures

  • ctg/scf/singleton stats

ABYSS

 # single reads; one library
 # getting the best kmer size
 ABYSS -k31 frag_12.fastq -o contigs.fa > ABYSS.log
 perl -e 'foreach $k (21,23,25,27,29,31,33,35,37,39,41,43,45,47,49,51) { print "ABYSS -k$k frag_12.fastq -o frag.K$k.fa\n" }'
 perl -e 'foreach $k (21,23,25,27,29,31,33,35,37,39,41,43,45,47,49,51) { print "lenseq frag.cor.K$k.fa | getSummary.pl -nh -i 1 -t K$k\n" }' > ABYSS.summary
 #paired & single reads
 abyss-pe -j2 k=31 n=10 name=ecoli lib='lib1 lib2' lib1='lib1_1.fa lib1_2.fa' lib2='lib2_1.fa lib2_2.fa' se='se1.fa se2.fa'
 ##############################

 #paired reads; multiple libraries; n: minimum number of links between 2 contigs in a scaffold
 abyss-pe k=31 n=5 name=genome lib='frag short' frag='frag_1.fastq frag_2.fastq' short='short_1.fastq short_2.fastq' aligner=bowtie >& abyss-pe.log
 #paired reads; multiple libraries; n: minimum number of links between 2 contigs in a scaffold
 abyss-pe k=31 n=5 name=genome lib='frag short' frag=frag_12.cor.fastq short=short_12.cor.fastq aligner=bowtie >& abyss-pe.log

ALLPATHS-LG

 The resulting draft genome assemblies have good accuracy, short-range contiguity, long-range connectivity, and coverage of the genome. 
 In particular, the base accuracy is high (≥99.95%) and 
 the scaffold sizes (N50 size = 11.5 Mb for human and 7.2 Mb for mouse) approach those obtained with capillary-based sequencing
 Good assemblies definition: ctgLen=~20–100 kb ; scfLen=~10 Mb
 Libraries,insert_types*  Fragment_size(bp)  Read_length(bp)  Sequence_coverage(×)  Required  Protocols
 Fragment                 180                ≥100             45                    Yes       existing ; try to improve high GC-content reg 
 ShortJump                3,000              ≥100             45                    Yes       Illumina 
 LongJump                 6,000              ≥100             5                     No        SOLiD EcoP15I based 
 FosmidJump               40,000             ≥26              1                     No        “ShARC” and “Fosill” developed by BROAD
  • Compile:
 #wget ftp://ftp.broadinstitute.org/pub/crd/ALLPATHS/Release-LG/LATEST_VERSION.tar.gz
 wget ftp://ftp.broadinstitute.org/pub/crd/ALLPATHS/Release-LG/latest_source_code/LATEST_VERSION.tar.gz
 tar xzvf LATEST_VERSION.tar.gz
 cd allpathslg-*
 autoconf 
 ./configure --with-boost=/fs/szdevel/core-cbcb-software/Linux-x86_64/  
 #ls -l /fs/szdevel/core-cbcb-software/Linux-x86_64/include/boost/
 #ll -l /fs/szdevel/core-cbcb-software/Linux-x86_64/lib/libboost_*
 make –j8 # use ‐j<n> to parallelize compilation
  • Compile issues : the static libs (.a) should be linked before the dynamic ones (-l)
 Fix: 
 g++ -fopenmp -imacros config.h -Wextra -Wall -Wno-unused -ansi -pedantic -Wno-long-long -Wsign-promo -Woverloaded-virtual \
 -Wendif-labels -O3 -ggdb3  -ftemplate-depth-50 -Wno-deprecated -Wno-parentheses -fno-stri ct-aliasing -mieee-fp -iquote . \
 -o ErrorCorrectJumpNew -pthread ErrorCorrectJumpNew.o \
 -L/fs/szdevel/core-cbcb-software/Linux-x86_64//lib libAllPaths3.a -lboost_system -lboost_filesystem  \
 -pthread -Wl,-rpath -Wl,/fs/szdevel/core-cbcb-software/Linux-x86_64//lib 

 -o CreateLookupTab -pthread CreateLookupTab.o \
 -o SamplePairedReadStatsOld -pthread SamplePairedReadStatsOld.o \
 -o SamplePairedReadStats -pthread SamplePairedReadStats.o \
 -o ErrorCorrectJump -pthread ErrorCorrectJump.o \
g++ -fopenmp -Wextra -Wall -Wno-unused -Wno-deprecated -ansi -pedantic -Wno-long-long -Wsign-promo -Woverloaded-virtual \
 -Wendif-labels -Wno-empty-body -Wno-parentheses -Wno-array-bounds -fno-nonansi-builtins -ftemplate-depth-50 -mieee-fp -fno-strict-aliasing -iquote . -imacros config.h -ggdb3  \
 -o ErrorCorrectJumpNew \
 -L/fs/szdevel/core-cbcb-software/Linux-x86_64//lib -R/fs/szdevel/core-cbcb-software/Linux-x86_64//lib \
 -pthread ErrorCorrectJumpNew.o libAllPathsLG.a -lboost_filesystem 
  • Configuration:
 set path=($path /fs/szdevel/core-cbcb-software/Linux-x86_64/packages/allpaths3/bin/)
 limit stacksize 100000
  • Sequence formatting: sort and add /[12] suffix if needed
 Picard
 java -jar /nfshomes/dpuiu/core-cbcb-software/Linux-x86_64/packages/picard-tools/FastqToSam.jar SAMPLE_NAME=in_12 QUALITY_FORMAT=Standard FASTQ=in_1.fastq FASTQ2=in_2.fastq OUTPUT=out_12.bam 
 java -jar /nfshomes/dpuiu/core-cbcb-software/Linux-x86_64/packages/picard-tools/SamToFastq.jar                                           INPUT=in_12.bam                    FASTQ=out_1.fastq SECOND_END_FASTQ=out_2.fastq
  • in_groups.csv & in_libs.csv files required
 echo group_name, library_name, file_name >! in_groups.csv
 echo frag,  frag,  chr14_fragment_12.bam >> in_groups.csv
 echo short,  short, chr14_shortjump_12.bam >> in_groups.csv
 echo long,  long,  chr14_longjump_12.bam >> in_groups.csv
 echo  library_name, project_name, organism_name, type,  paired, chr14_fragment_size, chr14_fragment_stddev, insert_size, insert_stddev, read_orientation, genomic_start, genomic_end >! in_libs.csv
 echo frag,    genome,       genome,        fragment, 1, 180, 20, , , inward, 0, 0 >> in_libs.csv
 echo short,   genome,       genome,        jumping,  1, , , 3000, 300, outward, 20, 81 >> in_libs.csv
 echo long,    genome,       genome,        jumping,  1, , , 35000, 3500, inward, 20, 56 >> in_libs.csv
  • prepare data
 BAMsToAllPathsInputs.pl DATA_DIR=$PWD PLOIDY=2 HOSTS=16 GENOME_SIZE=107349540 PICARD_TOOLS_DIR=/nfshomes/dpuiu/core-cbcb-software/Linux-x86_64/packages/picard-tools/
 or 
 Allpaths-LG-preprocess.amos 
  • run assembler
 (time RunAllPaths3G PRE=$PWD REFERENCE_NAME=. DATA_SUBDIR=. RUN=allpaths SUBDIR=run ERROR_CORRECTION=True ) >& RunAllPaths3G.log
 or
 Allpaths-LG-.amos
  • prepare data and run assembler in one subdirectory
 ~/bin/Allpaths-LG/Allpaths-LG-preprocess.amos -D PLOIDY=1 -D DATA_DIR=$PWD/mydata
 RunAllPaths3G PRE=$PWD REFERENCE_NAME=. DATA_SUBDIR=mydata RUN=RunAllPaths3G SUBDIR=run  >&! mydata.log
  • process run log
 cat RunAllPaths3G.log | grep RUN | p 'next unless (/^\[/ and $F[1]=~/^\w+/);shift @F; print join " ",@F; print "\n";' | sed -f RUN.sed | p 'print $.*10,": "; print "\$(BINDIR)/" unless(/^ln/); print $_;' > RUN.amos
 or 
 allpathsLogFilter.pl

Example: Ecoli: 0.05 simulated error ; 3 libs 50X,50X,5X
  step 2-30,32-36  : read error correction ; should run only once

  step program                     start     duration(5+ min)
    1  RunAllPaths3G               17:36:59  

    2  RemoveDodgyReads            17:37:03  
    3  PreCorrect                  17:38:08  9 
    4  FindErrors                  17:47:24  30   !!! most time consuming: 50% of the total time
    5  CommonPather                18:27:59  11
    6  MakeRcDb                    18:38:09  
    7  Unipather                   18:42:05  
    8  CommonPather                18:43:54  
    9  MakeRcDb                    18:48:50  
   10  FillFragments               18:50:09  
   11  CommonPather                18:51:07  
   12  MakeRcDb                    18:54:43  
   13  Unipather                   18:55:08  
   14  CloseUnipathGaps            18:55:29  
   15  LittleHelpsBig              18:58:23  
   16  ShaveUnipathGraph           19:00:19  
   17  ReplacePairsStats           19:01:44  
   18  RemoveDodgyReads            19:01:48  
   19  SamplePairedReadStats       19:02:48  
   20  UnipathPatcher              19:03:45  
   21  CommonPather                19:06:42  
   22  MakeRcDb                    19:10:40  
   23  Unipather                   19:10:41  
   24  FilterPrunedReads           19:10:43  
   25  CreateLookupTab             19:10:54  
   26  ErrorCorrectJump            19:11:41  
   27  SplitUnibases               19:12:26  
   28  MergeReadSets               19:12:28    
   29  GenerateLengthsFile         19:12:42  
   30  MakeRcDb                    19:12:52  
   31  MergeReadSets               19:13:09  
   32  UnibaseCopyNumber2          19:13:19  
   33  UnipathLocs3G               19:15:20  
   34  RemoveDodgyReads            19:15:38  
   35  ErrorCorrectJump            19:15:46  
   36  MergeReadSets               19:16:02  

   37  BuildUnipathLinkGraphs3G    19:16:05  
   38  SelectSeeds                 19:16:23  
   39  LocalizeReads3G             19:16:36  9
   40  MergeNeighborhoods1         19:25:30  
   41  MergeNeighborhoods2         19:26:48  
   42  MergeNeighborhoods3         19:26:50  
   43  DumpHyper                   19:27:06  
   44  RecoverUnipaths             19:27:12  
   45  FlattenHKP                  19:27:54  
   46  AlignPairsToFasta           19:27:56  
   47  RemoveHighCNAligns          19:28:12  
   48  MakeRcDb                    19:29:02  
   49  MakeScaffolds3G             19:29:06  
   50  PostPatcher                 19:29:36  
   51  FixSomeIndels               19:31:35  
   52  MakeReadLocs                19:37:53  
   53  ParseAssemblyReport         19:38:16
  • getting the corrected reads
 Allpaths-LG-postprocess.amos
 ...
 Fastb2Fasta IN=jump_reads_ec.fastb OUT=jump_reads_ec.fasta BREAKCOL=101
 ...
 Example: S aureus: 0.00 vs 0.02 simulated error ; 4 libs:180_45X,3000_45X,6000_5x,40000_1x
 more /fs/szattic-asmg5/dpuiu/HTS/Staphylococcus_aureus/Illumina.sim.180_45X.3000_45X.6000_5x.40000_1x/allpathsCor/README
 orig(e=0.00;0.02)                   len       allpathsCor(e=0.00;0.02)                        len:min;max      orientation
 ---------------------------------------------------------------------------------------------------------- 
 frag/1                    647052    100       filled_reads_filt.fasta   645445   644487       120  240         inward
 frag                      1294104   100       frag_reads_corr.fasta     1294093  1293557      100  100         inward
 short                     1294104                                                                              outward->inward
 medium                    143644                                                                               outward->inward
 long                      28728     100       long_jump_reads_ec.fasta  28716    17260*       96   100         inward  
 ----------------------------------------------------------------------------------------------------------
 short+medium              1437748   100       jump_reads_ec.fasta       1437188  872734*      97   100     
 short+medium+long         1466476   100       scaffold_reads.fasta      1465904  889994       96   100    
 frag+short+medium         2731852   100       reads_merged_ec.fasta     2731281  2166291      97   100     
 frag+short+medium+long    2760580   100       all_reads.fasta           2178124  1593104      96   240
 ----------------------------------------------------------------------------------------------------------
  • Notes
 On a simulated data set Ploidity = 1 or 2 did not help much
 the jump outies get reversed

CA

  • Version: 6.1
  • Web site
  • Input: 454, Sanger
  • Illumina format (Sanger or Illumina FASTQ)
 fastqToCA                      -libraryname prefix -type sanger            -fastq $PWD/prefix.fastq                              > prefix.frg
 fastqToCA -insertsize 300  30  -libraryname prefix -type [sanger|illumina] -innie -fastq $PWD/prefix_1.fastq,$PWD/prefix_2.fastq > prefix_12.frg
 fastqToCA -insertsize 3000 300 -libraryname prefix -type [sanger|illumina] -outie -fastq $PWD/prefix_1.fastq,$PWD/prefix_2.fastq > prefix_12.frg # long inserts
  • Command
 ~/bin/runCA -d . -s runCA.spec -p asm prefix*.frg >& runCA.log
  • 454
    • must use bog/mer params, otherwise lib insert size get reestimated; portion of scaffolds moved and rotated (compared to the ref seq)
 cat runCA.454.spec
 unitigger =                      bog
 ovlOverlapper =                  mer
  • Sanger/Illumina
 cat runCA.Sanger.spec
 unitigger =                      bog
 ovlOverlapper =                  ovl 
  • Large assemblies, run in parallel
  • Repeats: usually end up as degenerates
  • Breaks: seem to be caused by short tandem repeats (the multiple contig alignments are adjacent)

CA ShortReads assembly issues

Reads (~100bp) , high error

  • GC% bias, nonrandomness & redundancy in shortjump libs
 Use estimate genome size
 runCA genomeSize=...
 Redundancy/chimera detection script
 ~/dpuiu/bin/azimin/filter_library.sh
  • Set kmer thold manually to ~10 times the coverage
 74X cvg => 750 kmer thold
 runCA obtMerThreshold=750 ovlMerThreshold=750
  • Recompile the CA code
 cat AS_CGW/AS_CGW_dataTypes.h
  #define CGW_MIN_DISCRIMINATOR_UNIQUE_LENGTH 250
  • Avoid unitig breaks caused by fragment libries (~180bp ins)
 cat AS_BOG_MateChecker.cc
 //  if (globalStats[lib].samples < 10 )
 if (globalStats[lib].samples < 10 || globalStats[lib].stddev < 100 || globalStats[lib].mean < 500)

CA VeryShortReads assembly issues

Reads <40bp , high error

  • Recompile the CA code
 cat AS_global.h
   #define AS_READ_MIN_LEN  32
   #define AS_OVERLAP_MIN_LEN  30

Read correction

  • quake: better
  • OBT : takes too long, trims too much seq

Kmers

  • decrease kmer size 22->?

Unitigger

  • bog
  • increase utgErrorRate 0.015->?
  • Issues
    • Snps in the repetitive unitigs
  6 out of 529 unitigs don't align perfectly to genome => misassemblies
  data : 75bp error-free simulated reads 
  200bp lib: 25X cvg 
  6K lib   : 14X
  command: ~/bin/runCA -s ./runCA.spec  doOverlapBasedTrimming=0 unitigger=bog utgErrorRate=0.0 cgwErrorRate=0.0 cnsErrorRate=0.0 ovlErrorRate=0.0 -d . -p test test*.frg 
 show-coords -L 200 test.utg.delta | egrep -n '220002412853|220002412688'
 736581   736875  |        1      295  |      295      295  |    99.32  |  4639675      295  |     0.01   100.00  | NC_000913      utg220002412853 [CONTAINS]
 736741   737024  |        1      284  |      284      284  |   100.00  |  4639675      284  |     0.01   100.00  | NC_000913      utg220002412688 [CONTAINS]
 show-snps test.utg.filter-q.delta | grep 220002412853
 736815   A G   235       |       36       61  |    1    0  |  1  1  NC_000913 utg220002412853
 736851   A C   271       |       25       25  |    1    0  |  1  1  NC_000913 utg220002412853

Cgw

 filter out single fragment unitigs (most of them) and fix aStat from <1 to 1
  ~/bin/filterUnitigs.sh

Edena

  • Version 2.1.1
  • Web site
  • Input: Illumina ; unmated only !!!
  • Format: seq, fastq
  • Command:
 edena --readsFile  prefix.fastq --prefix prefix --minOverlap [20]   # overlap mode
 edena --edenaFile  prefix.ovl -p prefix  --overlapCutoff [22]       # assembly mode
  • Output: no information about the position of the reads in assembly !!!

Newbler

  • [2] more info ...
  • Input: 454, Sanger
  • Format: sff, seq/qual
  • The linker is automatically detected only in the sff files
  • The linker has to be "manually" removed from seq/qual files
  • Q: How to assemble paired reads from seq files?
  • A: Header line DIR=F, DIR=R : see "gatekeeper" command
  • No way to specify the library insert/std !!!
  • The input file order matters !!!
  • Can perform slightly better if CA OBT trimmings are used (Ex:Ecoli 454)
  • DeNovo commands:
 # sff input
 runAssembly -force -o dir *.sff

 # seq/qual files ; -p : explicit pair ends
 test -f prefix.seq
 test -f prefix.seq.qual
 runAssembly -o dir [-p] *.seq

 # step by step; multiple sequence types/insert size; order matters
 newAssembly .
 addRun -p Sanger.seq
 addRun -p 454.flx.sff
 addRun -p 454.tit.sff
 runProject .

  • RefMapper commands:
 #sff input
 runMapping -o . prefix.1con *.sff

 # step by step
 newMapping .
 addRun -p Sanger.seq
 addRun -p 454.flx.sff
 addRun -p 454.tit.sff
 setRef ref.1con
 runProject .
  • paired reads: must have the same template/library; dir=F|R
 Example:  
 >SRR001355.3635.1a template=2020+2021 dir=F library=SRX000348 trim=20-117
 ...
 >SRR001355.3635.1b template=2020+2021 dir=R library=SRX000348 trim=1-130
 ...
  • config file
 assembly/454AssemblyProject.xml
 Not tested: edit the params in this file and relaunch the assembly
  • viewer
 toAmos -ace 454Contigs.ace -m prefix.mates -o prefix.afg
 bank-transact -c -z -b prefix.bnk -m prefix.afg

SGA

  • Website
  • SGA (String Graph Assembler) is a de novo assembler for DNA sequence reads. It is based on Gene Myers' string graph formulation of assembly and uses the FM-index/Burrows-Wheeler transform to efficiently find overlaps between sequence reads.
  • Paper Efficient construction of an assembly string graph using the FM-index : Bioinformatics 2010
  • Author website
  • Git download
  • README
  • HELP
  • Compile
 ./configure --with-sparsehash=/fs/szdevel/core-cbcb-software/Linux-x86_64/ --with-bamtools=/fs/szdevel/core-cbcb-software/Linux-x86_64/packages/bamtools/
  • Example
 #!/bin/tcsh -x

 setenv THREADS 20

 setenv MINQUAL 4

 setenv MINOVL 45
 setenv MAXERR 0.04 
 setenv K 31
 setenv ITTERATIONS 10
 
 setenv k 27
 setenv MINCVG 3
 ##################################################################

 rm frag.pp.* default-*

 sga preprocess -p 1 -f $MINQUAL frag_?.fastq > frag.pp.fa
 sga index      -t $THREADS frag.pp.fa 

 sga correct    -k $K -i $ITTERATIONS -t $THREADS frag.pp.fa -e $MAXERR -m $MINOVL -o frag.pp.ec.fa
 sga index      -t $THREADS frag.pp.ec.fa 
 
 sga filter     -k $k -x $MINCVG frag.pp.ec.fa 
 sga overlap    -m $MINOVL -t $THREADS frag.pp.ec.filter.pass.fa 
 
 sga assemble   frag.pp.ec.filter.pass.asqg.gz

SOAPdenovo

  • Version: 1.05
  • Web site , Manual
  • Input: Illumina
  • Format: seq, fastq (Sanger/Illumina scale: no conversion neede)
  • Other BGI tools for read correction, snp calling, gap closing

Issues

  • SOAPdenovo scaff:
    • Floating point exception if the insert is too short
    • No output difference if the insert size given is longer than the real estimate

Options

 soapdenovo all –s config_file –K 25 –R –o graph_prefix
 soapdenovo pregraph –s config_file –K 25 [–R -d -p] –o graph_prefix
 soapdenovo contig –g graph_prefix [–R –M 1 -D]
 soapdenovo map –s config_file –g graph_prefix [-p]
 soapdenovo scaff –g graph_prefix [–F -u -G -p]
 -s	STR	configuration file
 -o	STR	output graph file prefix
 -g	STR	input graph file prefix
 -K	INT	K-mer size [default 23, min 13, max63]
 -p	INT	multithreads, n threads [default 8]
 -R		use reads to solve tiny repeats [default no]
 -d	INT	remove low-frequency K-mers with frequency no larger than [default 0] 
 -D	INT	remove edges with coverage no larger that [default 1]
 -M	INT	strength of merging similar sequences during contiging [default 1, min 0, max 3]
 -F		intra-scaffold gap closure [default no]
 -u		un-mask high coverage contigs before scaffolding [defaut mask]
 -G    INT     allowed length difference between estimated and filled gap
 -L		minimum contigs length used for scaffolding

Config file

  • Example 1:
 max_rd_len=100                        #maximal read length ; set to 100 by default; if not changed, longer reads get truncated

 [LIB]                                 #paired reads
 avg_ins=200                           #average insert size
 reverse_seq=0                         #if sequence needs to be reversed (FF instead of FR : not checked yet)
 asm_flags=3                           #in which part(s) the reads are used; 1:ctg 2:scf 3:ctg+scf 4:gapClosure
 rank=1                                #in which order the reads are used while scaffolding
 rd_len_cutoff=75                      #cut the reads from the current library to this length
 pair_num_cutoff=3                     #cutoff value of pair number for a reliable connection between two contigs or pre-scaffolds. ; 3:shortInserts;  5:longInserts   (don't seem to be able to decrease it under 3; larger values help with the repeats)
 map_len=32                            #minimun alignment length between a read and a contig required for a reliable read location. ; 32:shortInserts; 35:longInserts  (don't seem to be able to decrease it under 32; larger values help with the repeats)
 
 q1=/path/fastq_read_1.fq              #fastq file for read fwd; names in q1&q2 don't have to match but the positions do !!! 
 q2=/path/fastq_read_2.fq              #fastq file for read rev
 
 f1=/path/fasta_read_1.fa              #fasta file for read fwd
 f2=/path/fasta_read_2.fa              #fasta file for read rev

 p=/path/fasta_read_12.fa              #fwd followed by rev

 q=/path/fastq_read.fq                 #fastq file for read
 f=/path/fasta_read.fa                 #fasta file for read
 
 [LIB]                                 
 avg_ins=3000
 reverse_seq=1
 asm_flags=2
 rank=2
 pair_num_cutoff=5
 map_len=35
 
 q1=...
 q2=...

iid2uid mapping & posmap file

  • Example:
 cat s_1.unmated s_1.mates s_2.unmated s_2.mates s_3.unmated s_3.mates ... | p ' print $F[0],"\n"; print $F[1],"\n" if($F[1]);' | nl > s.iid2uid
 cat             s_1.mates             s_2.mates             s_3.mates ... | p ' print $F[0],"\n"; print $F[1],"\n" if($F[1]);' | nl > s.iid2uid
 paste s_1.fastq s_2.fastq | perl -ane ' next unless($.%4==1);  's/\@//g' ; @F=split /\s+/; print $F[0],"\n",$F[1],"\n";' | nl > s.iid2uid
 sort -nk2 -nk3 s.readOnContig  | grep -v ^read |  ~/bin/replaceFirstCol.pl -f $1.iid2uid | perl -ane '$F[4]=($F[3] eq "+")?"f":"r"; $F[3]=$F[2]+64; print join "\t",@F; print "\n";' > s.posmap.frgctg

links

  • Shows the links between contigs
 lenseq test.contig | egrep  '1376|2376'
 ctg        len
 ...
 1376       100    
 2376       69673  
 ...
 egrep '1376|2376' test.scaf
 #ctg       pos        dir len        #DOWN ctg:totLinks:avgLibMea 
 ...
 1376       109421     +   100        #DOWN 2376:52:55                #UP 2334:43:11 
 2376       109545     +   69673      #DOWN 2380:255:13               #UP 2334:255:8 1376:52:55 
 ...

 cat test.links | grep 2376 | grep 1376
 #ctg1      ctg2         dist    #Links  libMea
 1376       2376         34      32      240
 1376       2376         91      20      6054
 avgLibMea= (sum #Links*libMea)/(sum #Links)

Commands

  • All at once:
 SOAPdenovo all -s SOAPdenovo.config -o prefix      # all: do all assembly steps  
  • Step by step:
 1. (time SOAPdenovo pregraph -s SOAPdenovo.config -o prefix -K 23 -p 6 ) >>&  SOAPdenovo.log
 prefix.kmerFreq                                                                                # up to 256
 prefix.edge                                                                                    # FASTA format
 prefix.preArc 
 prefix.vertex                                                                                  # md5 sums ???
 prefix.preGraphBasic
 2. (time SOAPdenovo contig -g prefix -M 1 ) >>&  SOAPdenovo.log
 prefix.contig
 prefix.ContigIndex
 prefix.updated.edge
 prefix.Arc         
 3. (time SOAPdenovo map -s SOAPdenovo.config -g prefix -p 6 ) >>&  SOAPdenovo.log
 prefix.readOnContig
 prefix.peGrads
 prefix.readInGap
 4. (time SOAPdenovo scaff -g prefix -F ) >>&  SOAPdenovo.log               
 prefix.newContigIndex  
 prefix.links
 prefix.scaf
 prefix.scaf_gap
 prefix.scafSeq
 prefix.gapSeq

Run time

  • On Saureus simulated data set
 1. 216.460u 2.792s 0:52.27 419.4% 
 2. 0.425u   0.011s 0:00.50 86.0%    
 3. 59.921u  1.597s 0:21.21 290.0%   
 4. 6.113u   0.263s 0:06.22 102.4%   
  • Larger genomes ???

Output

  • No information about the position of the reads in assembly !!!
 cat scaffold1.filter-q.delta | ~/bin/delta2posmap.pl | sort -nk3 | head -20 | pretty

Adding more reads for scaffolding

Files to link:

 perl -e '@F=split /\s+/,"Arc contig ContigIndex edge kmerFreq peGrads preArc preGraphBasic vertex"; \
          foreach (@F) { print "ln -s ../SOAP-prev/*.$_\n" }'

GapCloser (works with SOAPdenovo)

 ~/szdevel/bin/SOAPGapCloser -b SOAPdenovo.config -a Bb.scafSeq -o Bb.scafSeq.new -t 12
 =>
 Bb.scafSeq.new      : FASTA file(Bb.scafSeq with fewer N's)
 Bb.scafSeq.new.fill : gap fill status
 Example:
 >scaffold2 175.2
 ...
 #begin  end     5'fill  3'fill  closed?
 55203   57185   0       23      0
 69718   71607   0       28      0
 79195   79219   24      0       1
 80681   80741   0       23      0
 81738   81876   0       37      0
 ...

GC vs Coverage correlation

 infoseq -description asm.K31.contig | p '/cvg_(\d+.\d+)/; print "$F[0] $F[1] $F[2] $1\n" ;' >! asm.K31.contig.infoseq 
 cat asm.K31.contig.infoseq | ~/bin/getCorrelationDescriptive.pl -i 2 -j 3 -min 100
 cat asm.K31.contig.infoseq | ~/bin/getCorrelationDescriptive.pl -i 2 -j 3 -min 1000
 ...


SOAPdenovo-prepare

  • Data Preparation Module generates necessary data for SOAPdenovo to run "map" and "scaff" steps from Contigs generated by SOAPdenovo or other assemblers with various length of kmer.
  • options:
   * -g [string] Prefix of output.
   * -K [int] Kmer length.
   * -c [string] Input Contigs FASTA. (Filename cannot be prefix.contig)
  • Example:
 /fs/szdevel/core-cbcb-software/Linux-x86_64/bin/SOAPdenovo-prepare -K 31 -c default-contigs.fa  -g genome  
 =>
 genome.ContigIndex
 genome.updated.edge
 genome.contig
 genome.Arc
 genome.conver
 genome.preGraphBasic
 SOAPdenovo map -s SOAPdenovo.config -g genome    -p 20
 SOAPdenovo scaff                    -g genome -F -p 20
  • Eaxmple: use it if the jumpreads are < contigging kmer size
 more ~/bin/SOAPdenovo-63mer.sh
 #!/bin/sh -x
 # Usage: SOAPdenovo-63mer.sh prefix ctgK scfK

 # pregraphing ...
 SOAPdenovo-63mer pregraph -s SOAPdenovo.config -K $2 -p 16 -o $1  >! SOAPdenovo.log

 # contigging ...
 SOAPdenovo-63mer contig   -g $1 -M 1                              >> SOAPdenovo.log

 # preparing ...
 mv $1.contig $1.contig.tmp 
 SOAPdenovo-prepare -K $3 -c $1.contig.tmp  -g $1                  >> SOAPdenovo.log

 # read mapping ...
 SOAPdenovo-63mer map      -s SOAPdenovo.config -g $1 -p 16        >> SOAPdenovo.log
 
 # scaffolding ...
 SOAPdenovo-63mer scaff    -g $1 -F                   -p 16        >> SOAPdenovo.log

Velvet

 Concerning read orientation, Velvet expects paired-end reads to come from opposite strands facing each other, as in the traditional Sanger format.
 If you have paired-end reads produced from circularisation (i.e. from the same strand), it will be necessary to replace the first read in each pair 
 by its reverse complement before running velveth.
  • Compile:
 make ’CATEGORIES=16’ \                   # max  libraries
       ’MAXKMERLENGTH=64’ \               
       ’OPENMP=1’ \                       # multithread
       ’BIGASSEMBLY=1’ \                  # more than 2.2 billion reads
       ’LONGSEQUENCES=1’                  # contigs longer than 32kb long
 make CATEGORIES=16 MAXKMERLENGTH=64 OPENMP=1 BIGASSEMBLY=1 LONGSEQUENCES=1
  • Input: 454 , Illumina, ABI SOLiD as well? , AssembledSequences
  • Format: seq, fastq (Sanger/Illumina style no conversion needed) all mates should be innies
  • 454:
    • does poorly
    • slightly better if the cvg is given
    • same results for fasta/fastq input
    • results get worse for higher cvg
  • Commands:
 # unmated reads
 velveth . <hash_size> -fastq -short *.fastq
 velvetg . -amos_file yes -read_trkg yes -exp_cov <cvg>

 # mated reads
 shuffleSequences_fastq.pl prefix_1.fastq prefix_2.fastq  prefix_12.fastq
 velveth . <hash_size> -fasta -short prefix.fastq -shortPaired prefix_12.fastq
 velvetg . -ins_length <mean> -ins_length_sd <std> -amos_file yes -read_trkg yes -exp_cov <cvg>
 #reference based
 bowtie prefix.1con  -1 prefix_1.fastq -2 prefix_2.fastq -l 28 -n 2 --best -I 100 -X 200 -p 12 --sam | sort > prefix.bowtie.sam
 velveth . 21 -reference prefix.1con -shortPaired -sam prefix.bowtie.sam
 velvetg . -exp_cov auto -ins_length 150 -scaffolding yes -exportFiltered yes -unused_reads yes

Aleksey's create_k_unitigs

  • Usage
    • genome8.umd.edu
 jellyfish count -m 31 -s 1073741824 -r -C -t 16 -o frag.k31.jf *.fa 
 mv -i frag.k31.jf_0 frag.k31.jf

 create_k_unitigs -C -l 64 -m 5 -M 5 -t 16 -o frag.k31 frag.k31.jf
 
 cat frag.k31_*.fa     > frag.k31.fa
 cat frag.k31_*.counts > frag.k31.counts
 rm frag.k31_*

 ~alekseyz/myprogs/getNumBasesPerReadInFastaFile.perl frag.k31.fa | sort -gr | head
    • cbcb
 /fs/szdevel/dpuiu/filter_illumina_data_quals.pl
 /fs/szdevel/dpuiu/k_unitig-0.0.1/bin/
 cat *fastq | /fs/szdevel/dpuiu/filter_illumina_data_quals.pl '#' > genome.seq

 /fs/szdevel/dpuiu/k_unitig-0.0.1/bin/jellyfish count -s 200000000 -m 31 -t 16 -r -C genome.seq
 /fs/szdevel/dpuiu/k_unitig-0.0.1/bin/error_correct_reads -d mer_counts.hash_0 -t 16 -m 3 frag_1.fastq

Jellyfish

 jellyfish count -m 18 -s 1073741824 --both-strands -t 16 -o frag.k18.jf frag_?.*fastq
 jellyfish merge frag.k18.jf_*  -o frag.k18.jf              
 rm frag.k18.jf_* 
 jellyfish histo frag.k18.jf > frag.k18.histo
 jellyfish stats     frag.k18.jf > frag.k18.stats
 jellyfish stats --f frag.k18.jf > frag.k18.fasta
 jellyfish stats --c frag.k18.jf | awk '{print $2,$1}' > frag.k18.tab

Scaffolding

Bambus

Comparative assemblers

Performance measures:

  • ctg/scf/singleton stats
  • a related finished genome(s)must be available
    • Q:which is the closest relative? A:align the reads to the refs and identify the one with the max number of hits
    • Q:how many repeats in the ref & how well are they assembled
    • Q: reference coverage: how many gaps are left?
    • comparative assembly to a very close/more distant relative

AMOScmp-shortReads

  • Web site
  • Version:
  • Input: 454, Illumina
  • Format: amos
  • 454 trimming:
    • alignment based trimming => longer/fewer contigs
    • OBT trimming => shorter/more contigs, fewer snps & breaks
    • lucy quality based trimming does not help much
  • Illumina trimming
    • Trim n bases at the 3'
    • Trim all bases with quality < n at the 3' & 5'
    • Delete all reads which contain N's
  • Commands:
 AMOScmp-shortReads prefix                           # 454    : use nucmer aligner
 AMOScmp-shortReads-alignmentTrimmed  prefix         # 454    : use nucmer aligner
 AMOScmp-shortReads -D DOSOAP=1 prefix               # Solexa : use soap aligner
  • Can use nucmer/soap for read alignment
 nucmer --maxmatch -l 16 -c 32

 soap -p 2 -r 2 -v 3 -g 3
 # p: parallel
 # r:2 report multiple occurances
 # v: max mismatch
 # g: max gap len
  • Breaks
    • Q: When the assembly is aligned back to the ref => how many breaks,snps ?
    • If several reads map partially to 2 different locations withing few hundred bp of one another & the CONTAINED reads in between align to multiple regions => excision of the repeat
    • by decreasing the "casm-layout -g" param from 1000 to 20(?) we can solve some of the problems

Maq

 maq.pl easyrun prefix.1con prefix.fastq                                    # single reads         
 maq.pl easyrun prefix.1con prefix.fwd.fastq prefix.rev.fastq -p -a [250]   # paired reads; max insert size defaults to 250bp ; NOT WORKING CORRECTLY !!! (0 paired reads reported)
  • Performs very well for close ref (>99% id); not that well for further ref (<98% id)

Newbler

  • See prev section
  • Commands:
 # reference based
 runMapping -o . prefix.1con *.sff

Other assemblers

ABBA

minimus2

 #!/bin/tcsh
 ln -s ../
 cat ref.seq qry.seq > prefix.seq
 toAmos -s prefix.seq -o prefix.afg
 set REFCOUNT=`grep -c ">" ref.seq`
 minimus2 -D REFCOUNT=$REFCOUNT -D MINID=94 -D OVERLAP=20 prefix


minimusN

 cat ref.asm/ref.scf.fasta | ~/bin/assignFastaIds.pl -p ref | tee ref.scf.fasta | ~/bin/scafffasta2fasta.pl  > ref.ctg.fasta
 cat qry.asm/qry.scf.fasta | ~/bin/assignFastaIds.pl -p qry | tee qry.scf.fasta | ~/bin/scafffasta2fasta.pl  > qry.ctg.fasta

 ~/bin/nucmer.amos -D REFN=18000 -D REF=ref.ctg.fasta -D SEQS=qry.ctg.fasta -D MINMATCH=20 -D MINCLUSTER=40 -D BREAKLEN=20 -D MAXGAP=20 ref-qry

 delta-filter -i 94 genome.filter-1.delta | /nfshomes/dpuiu/szdevel/SourceForge/AMOS/bin/delta2tab.pl | sort -nk1 -nk6 -nk7 

 ~/bin/AMOS/preMinimus2                 # to get qry breaks
 minimusN -D REFCOUNT=$REFCOUNT

Sequence aligners

Bowtie

  • No gapped alignments (yet)
 -n : max mismatches in seed (can be 0-3, default: -n 2)              (Soap??)
 -l : seed length for -n (default: 28)
 --best   : hits guaranteed best stratum; ties broken by quality
 --strata : hits in sub-optimal strata aren't reported (requires --best)
  • Create an index
 bowtie-build ref.fasta ref.fasta 
  • Aligned mated & unmated reads
 Example:
 # qry_1.fastq  & qry_2.fastq : mated reads
 # qry_0.fastq                : unmated reads

 bowtie  ref.fasta  -1 qry_1.fastq -2 qry_2.fastq -l 28 -n 2 -I 6000 -X 10000 --best  -p 8 >  qry_12.bowtie
 bowtie  ref.fasta     qry_0.fastq                -l 28 -n 2                  --best  -p 8 > qry_0.bowtie
  • --chunkmbs <int> max megabytes of RAM for best-first search frames (def: 64)
 increase it to 512 or 1024 in case of error

Maq / Bwa

  • bwa
  • index reference
 bwa index ref.fasta
  • short single reads
 bwa aln ref.fasta qry.fastq > qry.sai
 bwa samse ref.fasta qry.sai qry.fastq > qry.sam
  • short paired reads
 bwa aln ref.fasta qry_1.fastq > qry_1.sai
 bwa aln ref.fasta qry_2.fastq > qry_2.sai
 bwa sampe ref.fasta qry_1.sai qry_2.sai qry_1.fastq qry_2.fq > qry.sam
  • long reads
 bwa bwasw ref.fasta qry.fastq > qry.sam
  • Example
 bwa bwasw cChloroplast.fa test.fastq | sed 's/555//g' | pretty
 @SQ          SN:cChloroplast  LN:120481     
 match.fwd    0                cChloroplast  1  18  100M        *  0  0  TTATCCACCTATTGAAATAGATTCAACAGCGGCTAGATCCAGAGGAAAGTTGTGAGCATTACGTTCGTGCATAACTTCCATACCTAGGTTAGCACGATTA    ...     AS:i:100  XS:i:86  XF:i:2  XE:i:3  XN:i:0  
 5.fwd        0                cChloroplast  3  36  2S98M       *  0  0  NNATCCACCTATTGAAATAGATTCAACAGCGGCTAGATCCAGAGGAAAGTTGTGAGCATTACGTTCGTGCATAACTTCCATACCTAGGTTAGCACGATTA    ...     AS:i:98   XS:i:84  XF:i:3  XE:i:2  XN:i:0  
 3.fwd        0                cChloroplast  1  15  98M2S       *  0  0  TTATCCACCTATTGAAATAGATTCAACAGCGGCTAGATCCAGAGGAAAGTTGTGAGCATTACGTTCGTGCATAACTTCCATACCTAGGTTAGCACGATNN    ...     AS:i:98   XS:i:86  XF:i:2  XE:i:3  XN:i:0  
 5.rev        16               cChloroplast  2  36  1S99M       *  0  0  NNATCCACCTATTGAAATAGATTCAACAGCGGCTAGATCCAGAGGAAAGTTGTGAGCATTACGTTCGTGCATAACTTCCATACCTAGGTTAGCACGATTA    ...     AS:i:99   XS:i:85  XF:i:3  XE:i:2  XN:i:0  
 3.rev        16               cChloroplast  1  15  98M2S       *  0  0  TTATCCACCTATTGAAATAGATTCAACAGCGGCTAGATCCAGAGGAAAGTTGTGAGCATTACGTTCGTGCATAACTTCCATACCTAGGTTAGCACGATNN    ...     AS:i:98   XS:i:86  XF:i:2  XE:i:3  XN:i:0  
 ins.fwd      0                cChloroplast  3  40  2S48M2I50M  *  0  0  TAATCCACCTATTGAAATAGATTCAACAGCGGCTAGATCCAGAGGAAAGTNNTGTGAGCATTACGTTCGTGCATAACTTCCATACCTAGGTTAGCACGATTA  ...     AS:i:89  XS:i:75   XF:i:3   XE:i:2  XN:i:0  
 del.fwd      0                cChloroplast  3  41  2S47M2D49M  *  0  0  TAATCCACCTATTGAAATAGATTCAACAGCGGCTAGATCCAGAGGAAAGGTGAGCATTACGTTCGTGCATAACTTCCATACCTAGGTTAGCACGATTA      ...     AS:i:87   XS:i:73  XF:i:3  XE:i:2  XN:i:0  
 bwa bwasw -H cChloroplast.fa test.fastq | pretty  
 @SQ          SN:cChloroplast  LN:120481     
 match.fwd    0                cChloroplast  1  18  100M        *  0  0  TTATCCACCTATTGAAATAGATTCAACAGCGGCTAGATCCAGAGGAAAGTTGTGAGCATTACGTTCGTGCATAACTTCCATACCTAGGTTAGCACGATTA  ...       AS:i:100  XS:i:86  XF:i:2  XE:i:3  XN:i:0  
 5.fwd        0                cChloroplast  3  36  2H98M       *  0  0  ATCCACCTATTGAAATAGATTCAACAGCGGCTAGATCCAGAGGAAAGTTGTGAGCATTACGTTCGTGCATAACTTCCATACCTAGGTTAGCACGATTA    ...       AS:i:98   XS:i:84  XF:i:3  XE:i:2  XN:i:0  
 3.fwd        0                cChloroplast  1  15  98M2H       *  0  0  TTATCCACCTATTGAAATAGATTCAACAGCGGCTAGATCCAGAGGAAAGTTGTGAGCATTACGTTCGTGCATAACTTCCATACCTAGGTTAGCACGAT    ...       AS:i:98   XS:i:86  XF:i:2  XE:i:3  XN:i:0  
 5.rev        16               cChloroplast  2  36  1H99M       *  0  0  NATCCACCTATTGAAATAGATTCAACAGCGGCTAGATCCAGAGGAAAGTTGTGAGCATTACGTTCGTGCATAACTTCCATACCTAGGTTAGCACGATTA   ...       AS:i:99   XS:i:85   XF:i:3   XE:i:2  XN:i:0  
 3.rev        16               cChloroplast  1  15  98M2H       *  0  0  TTATCCACCTATTGAAATAGATTCAACAGCGGCTAGATCCAGAGGAAAGTTGTGAGCATTACGTTCGTGCATAACTTCCATACCTAGGTTAGCACGAT    ...       AS:i:98   XS:i:86  XF:i:2  XE:i:3  XN:i:0  
 ins.fwd      0                cChloroplast  3  40  2H48M2I50M  *  0  0  ATCCACCTATTGAAATAGATTCAACAGCGGCTAGATCCAGAGGAAAGTNNTGTGAGCATTACGTTCGTGCATAACTTCCATACCTAGGTTAGCACGATTA  ...       AS:i:89   XS:i:75  XF:i:3  XE:i:2  XN:i:0  
 del.fwd      0                cChloroplast  3  41  2H47M2D49M  *  0  0  ATCCACCTATTGAAATAGATTCAACAGCGGCTAGATCCAGAGGAAAGGTGAGCATTACGTTCGTGCATAACTTCCATACCTAGGTTAGCACGATTA      ...       AS:i:87   XS:i:73   XF:i:3   XE:i:2  XN:i:0  
 bwa bwasw -H cChloroplast.fa test.fastq | ~/bin/AMOS/sam2posmap.pl | pretty
 @SQ          SN:cChloroplast  LN:120481     
 match.fwd    cChloroplast  0  100  f  0  100  100  100.00  
 5. fwd       cChloroplast  2  100  f  2  100  98   100.00  
 3.fwd        cChloroplast  0  98   f  0  98   98   100.00  
 5.rev        cChloroplast  1  100  r  1  100  99   100.00  
 3.rev        cChloroplast  0  98   r  0  98   98   100.00  
 ins.fwd      cChloroplast  2  102  f  2  100  98   97.96   
 del.fwd      cChloroplast  2  98   f  2  100  98   97.96

Nucmer

  • Run on parallel on big data sets
 #!/bin/tcsh
 set REFN=`grep -c ">" ref.fasta`
 @ REFN/=20

 /nfshomes/dpuiu/bin/nucmer.amos -D REFSEQ=$PWD/ref.fasta -D QRYSEQ=$PWD/qry.fasta -D REFN=$REFN ref-qry

SOAP2

  • No gapped alignments
  • Create an index
 2bwt-builder ref.fasta 
  • Align mated & unmated reads
 -l : alignment seed
 -s : minimal alignment length 
 -n :  filter low-quality reads containing >n Ns before alignment, [5]
 -r : how to report repeat hits, 0=none; 1=random one; 2=all, [1]
 -v : maximum number of mismatches allowed on a read. [5] bp
 -g : one continuous gap size allowed on a read. [0] bp
 Example: don't forget "-2"
 soap2 -D ref.index -a qry_1.fastq -b qry_2.fastq -o qry_12.mated.soap2 -2 qry_12.single.soap2  -l 28 -v 2 -n 0 -m 6000 -x 10000 -p 8
 soap2 -D ref.index -a qry_0.fastq                -o qry_0.soap2                                -l 28 -v 2 -n 0                  -p 8

Alignment processing

Samtools

http://www.broadinstitute.org/gsa/wiki/index.php/The_Genome_Analysis_Toolkit http://www.broadinstitute.org/gsa/wiki/index.php/Converting_Illumina_output_to_BAM_files

Data sets

Sources

Escherichia coli str. K-12 substr. MG1655

  • SRA Study E coli Whole Genome Sequencing on 454 and Illumina (454 unpaired & Illumina reads)
  • SRA Study 454 sequencing of Escherichia coli str. K-12 substr. MG1655 genomic paired-end library (454 paired reads)
  • 29 complete strains: NCBI search: "Escherichia coli"[Organism] AND pt_default[prop] AND seqstat_complete[PROP]
  • /fs/szdata//ncbi/genomes/Bacteria/Escherichia_coli_*/
  • chromosome lengths 4.5-5.5Mbp
  • plasmids?
  • Ref (same species):
                len     gc%   
 NC_000913      4639675 50.79  Escherichia coli str. K-12 substr. MG1655, complete genome  (same substr?)  2.9%repeats
 NC_010468      4746218 50.87  Escherichia coli ATCC 8739, complete genome (99% id)
 NC_008253      4938920 50.52  Escherichia coli 536, complete genome (97% id)
  • Ref (same genus):
 NC_011740      4588711 49.94  Escherichia fergusonii ATCC 35469, complete genome (94% id)
 .                    elem       min    q1     q2     q3     max        mean       n50        sum            
 0cvg                 130        6      153    756    2085   18927      2307       7560       299947  (6.4% of the K12 genome not present in ATCC)        
 %id                  4929904    68.73  98.95  99.21  99.38  100.00     98.52      99         .   
  • Ecoli K12 vs 536 alignment : 97% identity => more distant
 .                    elem       min    q1     q2     q3     max        mean       n50        sum            
 0cvg                 375        2      134    461    1549   30645      1854.35    7094       695383  (14.98% of the K12 genome not present in 536)               
 %id                  4143854    79.11  96.81  97.48  97.88  100.00     97.17      97         .    
  • Ecoli K12 Repeats/Uniq regions (repeat-match based) : max uniq region is 138Kbp (the "best" we can do with short unmated reads) Media:Ecoli.K12-K12.png
  .                    elem       min    q1     q2     q3     max        mean       n50        sum            
  repeats.36bp+        701        36     42     57     132    3903       197.46     848        138420(2.9%)           
  repeats.100bp+       202        100    155    271    756    3903       550        1207       111011(2.4%) 
  repeats.200bp+       126        200    290    541    1208   3903       794.88     1221       100155(2.1%)
  uniq                 646        1      10     84     8366   138200*    6970.60    28028      4503010  
  • Longest repeat: 3903b : 3 complete + 8 partial(33%+)
 223979    227889  | 3903 2    | 3911 3902 | 99.23  | 4639675 3903 | 0.08 99.97  | NC_000913 NC_000913.3422674-3426576 [CONTAINS] 
 2725076   2727319 | 2    2245 | 2244 2244 | 99.60  | 4639675 3903 | 0.05 57.49  | NC_000913 NC_000913.3422674-3426576 
 2727589   2728971 | 2521 3903 | 1383 1383 | 100.00 | 4639675 3903 | 0.03 35.43  | NC_000913 NC_000913.3422674-3426576 
 3422674   3426576 | 1    3903 | 3903 3903 | 100.00 | 4639675 3903 | 0.08 100.00 | NC_000913 NC_000913.3422674-3426576 [CONTAINS] 
 3940039   3941416 | 3903 2526 | 1378 1378 | 99.64  | 4639675 3903 | 0.03 35.31  | NC_000913 NC_000913.3422674-3426576 
 3941605   3943857 | 2245 2    | 2253 2244 | 99.33  | 4639675 3903 | 0.05 57.49  | NC_000913 NC_000913.3422674-3426576 
 4033762   4037673 | 3903 2    | 3912 3902 | 99.41  | 4639675 3903 | 0.08 99.97  | NC_000913 NC_000913.3422674-3426576 [CONTAINS] 
 4164890   4166276 | 3903 2518 | 1387 1386 | 99.57  | 4639675 3903 | 0.03 35.51  | NC_000913 NC_000913.3422674-3426576 
 4166542   4168794 | 2245 2    | 2253 2244 | 99.11  | 4639675 3903 | 0.05 57.49  | NC_000913 NC_000913.3422674-3426576 
 4206378   4207764 | 3903 2518 | 1387 1386 | 99.57  | 4639675 3903 | 0.03 35.51  | NC_000913 NC_000913.3422674-3426576 
 4207944   4210196 | 2245 2    | 2253 2244 | 99.20  | 4639675 3903 | 0.05 57.49  | NC_000913 NC_000913.3422674-3426576 
  • Ecoli K12 Repeats (NCBI annotation)
 .                    elem       min    q1     q2     q3     max        mean       n50        sum            
 repeats              399        14     32     82     111    1443       191.69     980        76485          # much fewer than the ones I found
 genes                4485       14     465    813    1218   7077       922.17     1188       4135942        # ~ 62 genes (42Kb) CONTAINED by 42 annotated repeats
  • Ecoli K12 kmers
 23mers: most frequent occurance is 77
 31mers:                            46 
 41mers:                            11 
  • Ecoli K12 unique regions (Example)
 1745081-1952189
                                                                                                             # ~ 132 genes (75K) CONTAINED by 79 repeat-match repeats      
  • Location on disk:
 /fs/szattic-asmg4/dpuiu/HTS/Escherichia_coli/      


Read stats

  • 454 SRA
 .                    elem       min    max   mean    n50   sum         cvg     mea;std  q20Pos   SRA accession(s)
 454                  257,477    52     943   262     263   67640102    14.57   .                SRX012358,SRX012359
 454 paired           322,386    4      831   185     248   59677025    12.86   3500             SRX000348 (different study,only run) 
  • Illumina SRA
 .                    elem       min    max   mean    n50   sum         cvg     mea;std  q20Pos   SRA accession(s)
 Illumina             6,725,378  36     36    36      36    242113608   52.18   .        30      SRX007752 qual plot
 Illumina paired(37)  9,928,004  37     37    37      37    367336148   79.17   178      30;13   SRX012850 qual plot   
 Illumina paired(101) 20,635,060 101    101   101     101   .           449     168      50;13   SRX016044 SRR034509 qual plot  # based on alignments to ref, mea=~64
 Illumina paired(101) ?       101    101   101     101   .              449     150      50;13    ERX008638 
                                                                                               
 Illumina paired(36) ?                                                           500             SRX000430
 Illumina paired(36) ?                                                           200             SRX000429


  • Illumina company: data described in Illumina Technical Notes; complete dataset received from Amy Bouck-Knight(techsupport@illumina.com)
 .                    elem       min    max   mean    n50   sum         cvg     mea;std  q20Pos  min;max  
 Illumina paired(75)  20,304,466 75     75    75      75    1522834950  328     210;10   75;75   180;240    # Oct2010   *0.15 => 50X     # s_6 ; 53% of reads are error free 
 Illumina paired(35)  6,211,692  35     35    35      35    217409220   46      6054:280 35;35   5214;6894  # Oct2010   *0.60 => 28X     # s_7 ; 78% of reads are error free 
 Illumina paired(35)  4,851,382  35     35    35      35    169798370   36      8917;700 35;35   6817;11017 # Oct2010   *0.77 => 28X     # s_4 ; 78% of reads are error free
  • Illumina simulated
 .                    elem       min    max   mean    n50   sum         cvg     mea;std  q20Pos   
 Illumina paired(75)                                                            210
 Illumina paired(75)                                                            6054

Read alignments

 # ref: Ecoli K12
                      total         aligned                          aligned%  program
 454                  257477        257372                           99.96     nucmer -l 16 -c 32
 454 paired           322386        286115                           88.75     nucmer -l 16 -c 32
 Illumina             6725378       4109521                          61.10     soap -g 5 -v 5 
 Illumina paired      9928004       3819582(3663441 fwd+156141 rev)  38.47     soap -g 5 -v 5

454 (14.57X read cvg)

  • DeNovo assembly
 # ctg stats
                             ctgs   min   q1      q2      q3       max      mean    n50      sum         seqs    singl   0cvgSum  snps  breaks     comments
 CA.bog**                    176    1005  6116    17855   37563    169694   25899   44290    4558385     257477  1145    59607    1003  12         only contigs used for alignments; if deg used 0cvgSum=32455
 newbler.deNovo              274    100   1738    8645    25332    125168   16651   35805    4562444     257477  20255   68423    1242  5          
 velvet                      41859  45    54      67      96       9132     156     404      6566010(?)  257477  802     200706   45017 37         most uncovered regions 
  • DeNovo merge assembly (minimus2; singletons were merged in the contigs file)
 # ctg stats 
                       ctgs+sing    min   q1      q2      q3       max      mean    n50      sum         seqs    singl   0cvgSum  snps  breaks     comments
 CA.bog-newbler.deNovo       135    100   2036    19279   52988    224358   35628   79466    4809817     450     0       47585    1011  15


  • Reference based assembly (Ecoli K12)
 # ctg stats 
                             ctgs   min   q1      q2      q3       max      mean    n50      sum         seqs    singl   0cvgSum  snps  breaks     comments
 AMOScmp.alignmentTrimmed**  8      721   178178  548382  1208791  1574740  579935  1208791  4639482     257477  11472   48       1155  0          nucmer alignment trimmed reads
 AMOScmp.orig                269    243   4062    10640   23598    146792   17230   31488    4635098     257477  59369   9508     3338  1          original reads  
 AMOScmp.lucy                181    256   8180    17089   34961    161650   25608   40906    4635189     257477  45663   5839     2393  1          Lucy quality trimmed reads
 AMOScmp.OBT                 59     386   25713   51940   127336   280148   78607   135820   4637865     257477  723     1524     926   0          OBT trimmed reads

 newbler.refMapper           70     196   770     33983   88976    327077   65412   178569   4578847     257477  143     25805    1985  0          most uncovered regions ???
  • Reference based K12 & deNovo merge (minimus2; singletons were merged in the contigs file) : not much help
 # ctg stats
                       ctgs+sing    min   q1      q2      q3       max      mean    n50      sum         seqs    singl   0cvgSum  snps  breaks     comments
 CA.bog-AMOScmp.at.K12       24     694   27931   52358   62326    2123245  218921  1554570  5254104     184     0       122      1346  13
  • Reference based assembly stats (Ecoli ATCC)
                             ctgs   min   q1      q2      q3       max      mean    n50      sum         seqs    singl   0cvgSum  snps  breaks     comments
 AMOScmp.alignmentTrimmed*   199    34    695     5745    26504    292814   21784   75690    4335019     257477  28327   293438   2304  23         breaks are adjacent (tandem repeats?)
 AMOScmp.OBT                 314    77    914     6225    16704    166680   13756   37619    4319673     257477  20556   307393   1645  8          breaks are adjacent (tandem repeats?)

 newbler.refMapper           213    105   615     6653    25594    211153   19987   57867    4257433     257477  15725   333122   2385  46         breaks are adjacent (tandem repeats?)

  • Reference based assembly (Ecoli 536)
 # ctg stats 
                             ctgs   min   q1      q2      q3       max      mean    n50      sum         seqs    singl   0cvgSum  snps  breaks  comments
 AMOScmp.alignmentTrimmed    601    77    1080    3820    8977     61585    6525    12044    3921648     257477  46572   701339   1406  5        
 newbler.refMapper           476    101   747     4112    10299    97951    8184    18241    3895796     257477  35796   729086   3004  77
  • Read trimming
 .                    elem       min    q1     q2     q3     max        mean       n50        sum            
 CA.ORIG,CLR          252939     68     252    261    272    823        263.10     263        66547020       
 CA.OBTINITIAL        252939     67     250    260    271    724        260.52     261        65894538       
 CA.OBTCHIMERA,LATEST 252939     64     220    244    257    610        231.39     247        58528503       

 AMOScmp.K12          257372     33     241    252    263    342        246.44     254        63425475
 AMOScmp.ATCC         242665     32     239    252    262    337        244.32     253        59286793
 AMOScmp.536          223903     32     237    250    261    342        241.07     252        53977199
  • Repeat stats
                                 elem min  q1  q2  q3   max   mean    n50  sum
 genome                           701  36  42  57  132  3903  197.46  848  138420

 CA.bog                           516  36  40  49  78   848   72.84   79   37585   # may repeats end up in degenerates
 newbler.deNovo*                  576  36  41  52  88   1409  106.82  162  61528   # "long" repeats have only 1 copy in the assembly
 velvet                           123  36  39  43  56   128   51.82   48   6374    

 AMOScmp.alignmentTrimmed.K12*    680  36  42  59  133  3903  200.92  855  136627  
 AMOScmp.OBT.K12                  675  36  42  58  132  3903  201.00  926  135676  
 newbler.refMapper.K12            598  36  41  52  88   569   82.42   95   49288   # surprisingly "bad" for a comparative assembler

 AMOScmp.alignmentTrimmed.ATCC    601  36  42  58  121  3903  179.94  575  108146  
 AMOScmp.OBT.ATCC                 583  36  42  58  123  3903  182.45  581  106370  
 newbler.refMapper.ATCC           536  36  41  53  95   1208  106.75  156  57217   
  • Comments:
    • all repeats are CONTAINED
    • Many gaps match the repeats
    • Ref based assemblies to Ecoli ATCC & 536 contain many breaks
    • velvet assembly very fragmented; many regions covered by multiple contigs
  • Viewers

Apollo

454 paired (12.86X cvg) on FASTQ files

  • DeNovo assembly
 # contig stats
                             ctgs   min   q1      q2      q3       max      mean    n50      sum         seqs    singl   0cvgSum  snps  breaks     comments
 CA.bog*                     351    96    4154    9544    16800    96947    13097   21709    4597092     322386  4318    30577    1227  21         # error in the orig .frg files (FWD-FWD SRA lib => outie mates)  
 newbler.deNovo              801    100   1402    3701    7530     57354    5645    9907     4522066     322386  1094    86176    640   4

# scaffold stats
                             scf    min   q1      q2      q3       max      mean    n50      sum
 CA.bog*                     15     292   90673   198619  447960   882752   308205  707016   4623076
 newbler.deNovo              23     2062  2637    100587  210519   1824862  203995  598401   4691889                


  454 vs 454 paired CA.bog assembly qc
  • Reference based assembly(Ecoli K12)
 # contig stats
                             ctgs   min   q1      q2      q3       max      mean    n50      sum         seqs    singl   0cvgSum  snps  breaks     comments
 AMOScmp.alignmentTrimmed*   94     106   10818   31335   80022    303035   49345   90573    4638465     322386  40727   2552     848   2
 AMOScmp                     506    53    2633    6051    12524    61278    9156    16014    4633422     
 newbler.refMapper           114    100   7026    31322   55148    203278   40126   80905    4574379                                                # error: annotation missing from FASTA headers 
 newbler.refMapper.redo      801    100   1402    3701    7530     57354    5645    9907     4522066     322382  1094    86176    633   4           # much worse than newbler.refMapper ; 51% mates same ctg, 36% link , 11% FalsePair !!!
  • Repeat stats
                                 elem min  q1  q2  q3   max   mean    n50  sum
 genome                          701  36  42  57  132  3903  197.46  848  138420

 CA.bog.redo*                    643  36  42  56  140  3903  202.61  926  130277   !!!  longest repeat(3903 bp)     : 1 out of 3 copies present in assembly; 
                                                                                        2nd longest repeat(3240 bp) : 6 out of 7 copies present in assembly; 
 newbler.deNovo.redo             534  36  41  51  85   1811  116.04  245  61965   
 velvet                          194  36  39  47  69   848   67.57   69   13108

 AMOScmp.alignmentTrimmed.K12*   681  36  42  59  132  3903  200.68  855  136664  
 newbler.refMapper.K12.redo      534  36  41  51  85   1811  116.04  245  61965

454 paired (12.86X cvg) on SFF files

 # contig stats
                                 elem  min   q1    q2    q3     max    mean   n50    sum      q.0cvg  r.0cvg  1.0cvg  1.snps  1.breaks.all  1.breaks.1k+  
 CA.6.1                          351   6     3713  8594  17364  83842  13135  23470  4610499  47286   28839   54065   658     31            2             
 newbler.2.3                     477   1069  3507  6708  13167  61181  9287   14368  4429856  212847  160916  212847  268     13            3             
 newbler.2.5                     549   526   2619  5701  11142  72211  8176   13560  4488866  157609  116612  157609  226     11            1       
 # scaff stats
                                 elem  min    q1     q2      q3      max      mean    n50     sum      q.0cvg  r.0cvg  1.0cvg  1.snps  1.breaks.all  1.breaks.1k+  
 CA.6.1                          14    30345  67631  110633  659844  1216418  331422  686116  4639911  47272   28832   54051   660     366           10            
 newbler.2.3                     17    2023   5481   126476  204123  1958493  275782  705166  4688295  212847  160916  212847  268     474           101           
 newbler.2.5                     13    2060   36701  144055  517319  2057185  364272  711945  4735538  157609  116612  157609  226     548           61

Illumina.36len.52X

  • Input reads
 6,725,378 x 36bp
  • DeNovo assembly
 # ctg stats
                             ctgs  min  q1      q2      q3       max      mean    n50      sum      seqs     singl    0cvgSum snps  breaks
 edena                       7165  100  224     417     744      4375     568     819      4073189  6725378  4983572  591013  95    1

 velvet(k=21)*               1694  41   78      988     3856     35320**  2692    7060*    4561195  6725378  2662898  10859   973   8 
 velvet1.cor(k=21)**         1499  41   71      905     4390     34836*   3043    8038**   4562221  6725378                               # Oct2010 :longer

 SOAPdenovo                  5743  24   27      129     1046     13161    812     2503     4668239  6725378  3688149  99800   692   1
 SOAPdenovo.cor              3755  24   27      69      1390     30790    1232    4941     4628933  6725378
  • Reference based assembly(Ecoli K12)
                             ctgs  min  q1      q2      q3       max      mean    n50      sum      seqs     singl    0cvgSum snps  breaks 
 AMOScmp                     14    674  68206   245583  547319   1199735  331493  548739   4640911  6725378  4099119  16      1417  4          # only 3664073(54%) of seqs aligned to ref => 28X cvg
 maq**                       6     765  145073  727066  1444956  1976524  773274  1444956  4639645  6725378  4116513  23      23    0
  • Reference based assembly(Ecoli ATCC) : sharp decrease in assembly quality
                             ctgs  min  q1      q2      q3       max      mean    n50      sum      seqs     singl    0cvgSum snps  breaks
 AMOScmp*                    1530  36   95      532     2933     50248    2828    10506    4328273  6725378  4362159  329400  2837  29         # only 3281823(48%) of seqs aligned to ref => 25X cvg
 maq                         1600  14   100     512     2670     51703    2694    10283    4311361  6725378  4415635  349521  1047  37
  • Merged assembly
  .                           elem  min  q1      q2     q3     max        mean       n50       sum 
  velvet                      1694  41   78      988    3856   35320      2692      7060       4561195        
  AMOScmp.ATCC                1530  36   95      532    2933   50248      2828      10506      4328273        
  velvet-AMOScmp.ATCC         418   41   100     1110   9918   208338     11292     51437      4720083    
  • Repeat stats
                elem min  q1  q2  q3   max   mean    n50  sum
 genome          701  36  42  57  132  3903  197.46  848  138420

 edena           57   36  53  75  156  756   139.07  244  7927    
 SOAPdenovo      130  36  48  67  139  570   118.14  202  15358   
 velvet*         182  36  48  65  139  855   120.25  229  21885   

 AMOScmp.K12     681  36  42  59  132  3903  200.68  855  136664  
 maq.K12         670  36  42  60  140  3903  203.30  855  136213  

 AMOScmp.ATCC    590  36  42  57  112  3026  164.80  501  97230   ??? max repeat not assembled 
 maq.ATCC        579  36  42  58  122  2029  164.34  479  95154
  • Comments
    • ACGATGTGACGTACGCGTATGCTCGTATACACACGC appears more than 231K times in the input; does not align to Ecoli or any other genomes

Illuminap.37len.178ins.79X

  • DeNovo assembly
 # ctg stats
               ctgs   min q1   q2   q3   max   mean    n50  sum      seqs     singl   0cvgSum snps  breaks
 SOAPdenovo    33346  24  24   25   124  6125  155.08  596  5171181  9619686  7111896  84198  1929  3    
 velvet        8080   45  178  364  721  7544  561.01  908  4532926  9619686  6199264  95868  1214  2

Illuminap.101len.150ins.173X

  • INPUT:
 reads: 8,000,000
 mates: 4,000,000
 clr:   101bp
  • OUTPUT:
 #ctg stats:
 .                    elem       min    q1     q2     q3     max        mean       n50        sum            
 CA(OBT)              747        207    2204   4114   7508   35940      5962.97    8812       4454336
 SOAPdenovo           2789825    100    101    101    101    1116       101.32     101        282665113            
 velvet               73160      45     45     45     88     2282       87.06      117        6369253        
 #scf stats
                      elem       min    q1     q2     q3     max        mean       n50        sum            
 CA                   601        1016   2533   4817   9024   38235      7416.40    11317      4457256 
 SOAPdenovo           2789825    100    101    101    101    1116       101.32     101        282665113
 velvet

Illuminap.101len.150ins.59X.trimmed

  • Quality trimming:
    • N trimming: reads which contain N's were discarded
    • Q20 trimming: beginning/end bases Q20- were deleted
  • INPUT:
 reads: 3,013,500
 mates: 1,506,750
 avgClr:   91bp

 #ctg stats:
 .                    elem       min    q1     q2     q3     max        mean       n50        sum            
 CA                   916        211    1989   3357   5990   44653      4712.96    6317       4317070 
 SOAPdenovo           64582      100    100    101    104    2209       147.10     101        9500101 
 velvet(k31)          915        61     238    2191   7008   48470**    4970.98    12083**    4548449
 #scf stats
                      elem       min    q1     q2     q3     max        mean       n50        sum            
 CA                   738        1023   2278   4135   7301   44653      5854.51    8275       4320630
 SOAPdenovo           60942      100    100    101    101    5705       168.40     125        10262880
 velvet(k31)          151        633    6518   10088  18197  48338**    13072.10   18197**    1973887

Illuminap.101len.150ins.150X.cor

  • INPUT
 reads:  8,835,962           #  20,635,060 reads originally
 mates:  4,417,981
 avgClr: 79bp
 mea:    150
 #ctg stats
 .                    elem       min    q1     q2     q3     max        mean       n50        sum         0cvgSum snps  breaks rearrangements   
 CA                   470        573    2986   6181   12285  68568      9614.45    15688      4518792     100041  348   20     3 
 SOAPdenovo100+       596        100    260    3233   10238  73870      7609.43    18141      4535220     91689   25    1         
 velvet100+           262        103    374    5487   26564  221091**   17346.07   46409**    4544670     14018   405   5
 # scf stats
 .                    elem       min    q1     q2     q3     max        mean       n50        sum       rearrangements
 CA                   378        1017   3334   7108   15206  70497      11959.34   21457      4520632   3          
 SOAPdenovo           165        100    252    2713   35162  410074     27923.05   94982      4607303   0          
 velvet100+           174        103    198    1919   30793  413929**   26175.74   95373**    4554578   4         
  • Reference based assembly(Ecoli K12)
                          ctgs  min  q1      q2      q3       max      mean    n50      sum      seqs     singl    0cvgSum snps  breaks 
 AMOSCmp.soap             8     769  299915  345273  1100345  1444961  579962  1100345  4639697                                            # soap2  -r 2  -v 2 -n 0 -l 28 
  • Reference based assembly(Ecoli ATCC)
                           ctgs  min  q1      q2      q3       max      mean    n50      sum      seqs     singl    0cvgSum snps  breaks 
 AMOSCmp.soap100+          1024  100  431     1348    4811     56348    4199    11899    4300027                                            # soap2  -r 2  -v 2 -n 0 -l 28    => 0cvg: 1033 regions; 419859 bp
 AMOSCmp.nucmer100+        428   100  210     1246    12466    233619   10142   35998    4341162                                            # nucmer -c 40 -l 20 -b 200 -g 90 => 0cvg: 241  regions; 408109 bp
  • Merged assembly
  .                             elem       min    q1     q2     q3     max        mean       n50        sum            
  velvet100+                    262        103    374    5487   26564  221091**   17346      46409**    4544670        
  AMOSCmp-ATCC.nucmer100+       428        100    210    1246   12466  233619     10142      35998      4341162  
 
  velvet-AMOScmp.ATCC.nucm100+  104        114    1382   14570  52256  413910     45545      121678     4736715

IlluminaTechnicalNotes (Illumina results)

  • Metrics: N50 , Max, Genome coverage
  • Factors
    • Cvg: no improvement beyond 50X :
    • ReadLen: reads beyond 36bp(100bp exp) don't help
    • Inserts: insert should be longer than longest repeat
 insertLen    readLen    readCvg  elem                                   maxScf*               n50Scf**              genomeCvg***       #readsSampled   #mateSampled
 200          2*75       50X      ?                                      223,000               97,000                99.58              3,045,862(49X)  1,522,931
 200+6K       2*75+2*35  50X+28X  ?                                      2,100,000             1,300,000             99.07              4,099,798(31X)  2,049,899
 200+9K       2*75+2*35  50X+28X  ?                                      4,500,000             4,500,000             99.69              3,736,240(28X)  1,868,120
    • Quality: best results for N/Failed_Chastity/s35 filter

IlluminaTechnicalNotes (CBCB results)

  • Compare given qualities with the computed ones
    • sample reads
 ~/bin/sampleFastq12.pl -r 0.0070 -noN -count 10000 ../s_6_1_export.sample.fastq ../s_6_2_export.sample.fastq Ecoli_1.fastq Ecoli_2.fastq
 fastq2seq.pl < Ecoli_1.fastq >! Ecoli_1.seq
 cat original.count 
 #fwd                            rev                             mates
 s_2_1_3kb_sequence.txt          s_2_2_3kb_sequence.txt          21563283
 s_2_1_8kb_sequence.txt          s_2_2_8kb_sequence.txt          198377
 ...
 cat original.count | p 'next if(/^#/); $c=10000; $r=(($c*1.05)/$F[2]); print "~/bin/sampleFastq12.pl -r $r -count $c  original/$F[0] original/$F[1] original_sample/$F[0] original_sample/$F[1]\n";'


    • given qualities => avg error
 cat Ecoli_1.fastq | fastx_quality_stats | ~/bin/quality2error.pl -i 5 | nl >!  Ecoli_1.fastq.pos_qual
 cat Ecoli_1.fastq.pos_qual | getSummary.pl -i 1 | perl ~/bin/transpose.pl | grep mean  => 0.0019493
    • estimate qualities : based on alignment to reference : ~ 0.2% (probably lower than it is)
    • alignments snps => avg error
 nucmer -maxmatch -l 12 -c 12  ~/Escherichia_coli/Data/1con/Ecoli.K12.1con Ecoli_1.seq -p Ecoli_1
 cat Ecoli_1.delta | delta-filter-max.pl | ~/bin/deltaextend.pl | show-snps.pl -1 -H  | count.pl -p 10000 -i 3 | sort -n >! Ecoli_1.align.pos_qual
 perl -e '$n =`wc -l Ecoli_1.filter-q.extended.snps | cut -f1 -d " "`; $e=($n/(75*10000)); print $e,"\n"  => 0.022      


Ecoli.210.png Ecoli.6k.png Ecoli.9k.png

  • Estimate library insert sizes
         total    mated     single    single.both.aligned   single.both.compressed  single.both.expand
 210     20000    17780     783       30                    12                      18
 6k      20000    14360     3222      1434                  560                     856
 9k      20000    14130     3508      1906                  744                     1156


  • Error correction:
 quake.py -f Ecoli.ls -k 18 -p 16
 cat Ecoli.ls
    Ecoli_1.fastq Ecoli_2.fastq 
    Ecoli_1.6k.fastq Ecoli_2.6k.fastq 
    Ecoli_1.9k.fastq Ecoli_2.9k.fastq 

 original(mates)  corrected(mates)  corrected(fwd)  corrected(rev)  deleted
 1,522,931        1,241,547         138,323         88,984          335,461  
 2,049,899        1,665,847         196,868         171,832         399,404
 1,868,120        1,528,727         173,005         146,659         359,122
  • velvet
 #scf100+ stats
 .                                elem       min    q1     q2     q3     maxScf*    mean       n50Scf**   sum        genomeCvg*** 
 200                              177        100    168    1427   31804  325,889    25729      95,446     4554080    99.91           
 200+6K                           79         100    121    182    623    1,591,085  59027      1,590,440  4663117
 200+9k                           78         100    130    190    734    1,637,906  59820      1,093,506  4665962
 #ctg100+ stats
 insertLen                        elem       min    q1     q2     q3     maxCtg     mean       n50Ctg     sum            
 200                              312        100    596    5818   22311  110,215    14579      36,329     4548539        
 200+6K                           259        100    475    7990   28357  165,821    17911      42,905     4638953
 200+9k                           248        100    537    8388   25761  186,539    18648      45,601     4624717
 # cvg computed using : nucmer -maxmatch Ecoli.1con Ecoli.ctg.fasta -p 1con-ctg  ; delta2cvg.pl < 1con-ctg.delta -M 0 | getSummary.pl -i 4  
  • CA
 #scf100+ stats
 .                                elem       min    q1     q2     q3     maxScf     mean       n50        sum            
 200                              389        1037   3683   7477   13796  71,906     10484      15837      4078105       # minRead=64;minOvl=40;minUtg=1000 (default)
 200.redo                         420        208    2443   4372   8100   39,715     6343       9202       2664254       # minRead=32;minOvl=30;minUtg=500
 200+6k                           ?                                                                                     # minRead=32;minOvl=30;minUtg=500  : run for a very long time ; killed
 200+6k.redo2                     166        75     1298   1904   8579   101,429    6257       14354      1038602       # minRead=32;minOvl=30;minUtg=500;utgErrorRate=0.03 ; lots of degenerates
 #ctg100+ stats
 .                                elem       min    q1     q2     q3     maxCtg     mean       n50        sum            
 200                              657        104    2570   4773   8167   39,986     6199       8626       4072659 
 200.redo                         454        75     2322   4153   7505   35,904     5866       8744       2663112 
 200+6k                           ?                                                                                     # minRead=32;minOvl=30;minUtg=500  : run for a very long time ; killed
 200+6k.redo2                     612        35     215    1132   1827   4,994      1195       1904       731055        # minRead=32;minOvl=30;minUtg=500;utgErrorRate=0.03  ; lots of degenerates
  • Note
  • Shorter velvet ctgs/scf on corrected reads: the input reads are already high quality !!!

IlluminaTechnicalNotes sim data err=0.0

 insertLen    readLen    readCvg     
 200+6K       2*75+2*35  50X+28X     
 200+6K       2*75+2*75  50X+28X     
  • velvet
 #scf100+ stats
 .               elem       min    q1     q2     q3     max        mean       n50        sum        
 velvet.35       72         100    133    182    531    4636779    64823      4636779    4667231
 velvet.75       72         100    129    182    531    4636870    64822      4636870    4667211    
 #ctg100+ stats
 .               elem       min    q1     q2     q3     max        mean       n50        sum        
 velvet.35       154        100    191    1919   42330  263156     30158      93526      4644318
 velvet.75       145        100    178    1331   45218  263151     32092      98728      4653398
  • CA
    • CA.35 : cgw would take days to complete; Solution: delete 526,644 reads that assemble into single fragment unitigs (7% of total reads)
 #scf100+ stats
 .               elem       min    q1     q2     q3     max        mean       n50        sum   
 CA.35           20         7383   81163  122901 359340 729797     222118     409560     4442362     
 CA.75           1          4640849                     4640849                                     
 #ctg100+ stats
 CA.35           97         6687   14090  29769  57870  326996     44421      67366      4308861
 CA.75           47         102    14731  68369  128240 515019     98614      176651     4634873

Illuminap.64len.475ins.50X

  • Simulated data : maq simulator :
 maq simulate -d 475 -s 47 -1 64 -2 64 -N 1812500 -r 0.001 Ecoli_1.fastq Ecoli_2.fastq Ecoli.1con Ecoli.simupars.dat
 soap2 -D Ecoli.1con.index -a Ecoli_1.fastq -b Ecoli_2.fastq -M 0 -o Ecoli_12.mated.soap2 -2 Ecoli_12.single.soap2 -m 375 -x 575 -p 20 -r 2
 cat *soap2 | ~/bin/AMOS/soap2posmap.pl | ~/bin/posmap2cvg.pl -M 0 | getSummary.pl -i 4

 .       elem  min  q1  q2  q3  max  mean  n50  sum   
 0cvg    1382  1    2   3   5   84   4.71  5    6512  #due to mutation
 reads:    3,625,000  
 clr:      64 bp
 mea;std : 475;47 
 #ctg stats
 .                          elem       min    q1     q2     q3     max        mean       n50        sum  
 velvet100+                 261        100    441    7429   25373  152351     17468      41524      4559162
 CA.ctg100+                 0                                                                                #no ctg/scf just deg max 200; is cvg too low?

 #scf stats
 velvet100+                 148        100    158    923    33253  327108     30850      132780     4565870
  • Reference based assembly(Ecoli K12)
                            elem       min    q1     q2     q3     max        mean       n50        sum  
 AMOSCmp.nucmer100+         1                                      4639681                          4639681 
  • Reference based assembly(Ecoli ATCC)
                            elem       min    q1     q2     q3     max        mean       n50        sum      
 AMOSCmp.nucmer100+         510        100    296    1741   11087  105786     8495       27761      4332605             # nucmer -c 28 -l 14              => 0cvg: 334 regions; 401485 bp
  • Merged assembly
                            elem       min    q1     q2     q3     max        mean       n50        sum      
 velvet-AMOSCmp.nucmer100+  138        114    1861   17205  50382  268321     39660      105786     5473097             # total length is >> genomeLength (some duplication going on)

Illuminap.64len.475ins.50X-64len.8000ins.10X (60X cvg)

 reads:    3,625,000  + 725,000
 clr:      64 bp
 mea;std : 475;47       8000;800
 #ctg stats
 .                          elem       min    q1     q2     q3     max        mean       n50        sum  
 SOAPdenovo100+             576        100    249    3249   9909   73,093     7893       21083      4546797
 velvet100+                 179        100    223    2955   35078  240,045    25933      83796      4642027 
 #scf stats
 SOAPdenovo100+             241        100    151    730    6746   492338     19669      219830     4740402  # pair_num_cutoff=default
 SOAPdenovo100+             213        100    114    151    296    2,142,392  22266      1430222    4742568  # pair_num_cutoff=50
 velvet100+                 75         100    133    204    623    4,406,037  62160      4406037    4661969

Staphylococcus aureus

  • SRA Study Staphylococcus aureus Sequencing on Illumina
  • 22 complete strains: NCBI search: "Staphylococcus aureus"[Organism] AND pt_default[prop] AND seqstat_complete[PROP]
  • /fs/szdata//ncbi/genomes/Bacteria/Staphylococcus_aureus_*/
  • chromosome lengths 2.7-2.9Mbp
  • plasmids? (2-3)
  • Ref:
 id                len     gc%    desc                    
 NC_010079         2872915 32.76  Staphylococcus aureus subsp. aureus USA300_TCH1516, complete genome  (most related to Illumina data set)
 NC_003923         2820462 32.83  Staphylococcus aureus subsp. aureus MW2, complete genome
 NC_007622         2742531 32.78  Staphylococcus aureus RF122, complete genome

 NZ_AASB00000000   2810505 32     Staphylococcus aureus subsp. aureus USA300_TCH959, 256 contigs
 USA300-MW2 
 .                 elem       min    q1     q2     q3     max        mean       n50        sum            
 %id               2873390    79.28  98.93  99.30  99.54  100.00     98         99         284357849.9    
 0cvg              124        2      60     430    1357   18282      1149       2539       142568         
  • Repeats (Saureus USA300)
 .                    elem       min    q1     q2     q3     max        mean       n50        sum            
 36bp+                667        36     44     62     98     5016       125        191        83788         
 100bp+               158        100    119    158    254    5016       348        746        55049         
 200bp+               56         201    253    324    746    5016       735        1506       41185
  • Uniq (Saureus USA300)
 .                   elem       min     q1     q2     q3     max        mean       n50        sum            
 36bp+               623        1       10     75     820    126818     4467       34787      2783139        
 100bp+              142        1       76     1512   32659  180152     19801      74137      2811878        
 200bp+              48         1       221    35708  88217  328320     58812      145211     2823011        

Read stats

 .                      reads       min    max    mean       n50        sum              cvg      SRA accession(s)
 454                    391,495     51     857    273        275        107151210        37.29    SRX002328 strain USA300_TCH959 HMP0023 

 454 paired             490,520     1      1323   134        182        65822848         22.95    SRX002327 strain USA300_TCH959 HMP0023 ; NOMINAL_LENGTH=2750 NOMINAL_STDEV=250

 Illumina               2,739,566   36     36     36         36         98624376         34.32    SRX007668  qual plot
 
 Illumina paired end    8,982,084   36     36     36         36         323355024        112.55   SRX007696  qual plot  #  NOMINAL_LENGTH=175

 Illuminia jumping lib  17,678,908  37     37     37         37         654119596        227      SRX007711 # NOMINAL_LENGTH=300, ORIENTATION=5'3'-3'5'; soap estimate 3538
 Illumina paired        30,597,352  101    101    101        101        3090332552       1075     SRX007714 # NOMINAL_LENGTH=300, NOMINAL_SDEV=22.253, ORIENTATION=5'3'-3'5  ; CA estimate mea/std=170/21; strain USA300_TCH1516

454 stats (37.29X read cvg)

  • DeNovo
 .                       ctgs min  q1     q2      q3      max     mean       n50     sum      
 CA.6.0.bog              31   1471 16316  51985   142506  318772  89171      157559  2764330  
 CA.6.1.bog              47   1066 6623   26392   73408   309139  58908      145306  2768666    # fewer degenerates compared to  CA.6.0.bog
 newbler.2.3.deNovo      85   104  203    1176    19635   295958  32888      157201  2795541  
 newbler.2.5p1.deNovo*   46   105  231    3087    56818   546353* 60730      296002* 2793599
  • Reference based(Saureus USA300_TCH1516 (diff strain))
 .                       ctgs min  q1     q2      q3      max     mean       n50     sum   
 newbler.2.3.refMapper   183  103  630    3737    18738   117468  14374      42301   2630491
 newbler.2.5p1.refMapper 186  103  589    3740    17184   117464  14139      43130   2629763

454 paired stats (22.95X read cvg)

  • Data
                       reads   min    q1     q2     q3     max        mean       n50        sum            
 sff(original)         334241  36     201    256    277    362        235        264        78432227      
 sffToCA(adaptor free) 325555  51     103    148    208    358        157        185        51225615   # 58723 mates
  • DeNovo
 # ctg stats
 .                    ctgs min  q1     q2      q3      max     mean       n50     sum      
 CA.6.0.bog           11   278  47961  194288  508135  590074* 255272     508135* 2808001  
 CA.6.1.bog           18   238  21014  135971  239466  567548  155836     277888  2805055

 newbler.2.3.deNovo   544  100  810    2652    7672    33434   5126       10865   2788673  
 newbler.2.5p1.deNovo 100  103  295    3287    39467   229053  27879      78379   2787870
 # scf stats
 .                    scfs min  q1     q2      q3      max     mean       n50     sum            
 CA.6.0.bog           6    278  47961  194288  1035529 1410221 468016     1410221 2808101        
 CA.6.1.bog           6    284  21014  173065  1032129 1458733 467554     1458733 2805325
 
 newbler.2.3          16   2042 2173   2767    110212  1409442 176373     1037981 2821966
 newbler.2.5p1.deNovo 8    2475 20731  110137  1030785 1408642 349895     1408642 2799157
  • Reference based(Saureus USA300)
 .                    ctgs min  q1     q2      q3      max     mean       n50     sum      
 newbler.2.3.refMapper 206 103  556    3098    15366   117487  12749      40687   2626469

Illumina stats (34.32X read cvg)

  • DeNovo
 .                 ctgs  min  q1     q2     q3      max     mean   n50     sum      seqs     singl    0cvgSum snps  breaks
 edena             3956  100  207    422    851     13908   656    1040    2597617  2739566  ?        315399  18    1
 SOAPdenovo*       5814  24   45     164    624     13087   503    1331    2925517  2739566  ?        69547   298   1
 velvet            3477  45   166    464    1054    10468   812    1528    2825440  2739566  ?        100722  638   17
  • Reference based(Saureus USA300)
 .                 ctgs  min  q1     q2     q3      max     mean   n50     sum      seqs     singl    0cvgSum snps  breaks
 AMOScmp           81    36   5859   20119  52879   196907  35474  75670   2873401  2739566  1003517  376     649   3        # only 2126008(77%) of seqs aligned to ref => 26X cvg
 maq**             41    36   10188  33799  114655  341537  70064  154157  2872626  2739566  955336   369     43    0   
  • Reference based(Saureus MW2)
 .                 ctgs  min  q1     q2     q3      max     mean   n50     sum      seqs     singl    0cvgSum snps  breaks
 AMOScmp           1199  36   88     366    2000    48748   2268   8866    2720299  2739566  1118637  152285  2369  19      # only 1965762(71%) of seqs aligned to ref => 24X cvg
 maq*              1052  36   91     364    2111    64379   2576   10270   2710270  2739566  1100695  167184  2357  21


Illumina paired stats (112.55X read cvg; avgInsert=~60bp)

  • Read alignments
 73% of the reads align by "soap -g 5 -v 5 -r 2 -f 0"
 3368102 fwd 
 3210408 rev
 6578510 total
  • DeNovo
 #ctg stats
 .                 ctgs  min  q1     q2     q3      max     mean   n50     sum      seqs     singl    0cvgSum snps  breaks
 edena             4636  100  216    388    707     6754    544    782     2526187  2739566  ?        385985  88    2       # most 0cvg regions
 SOAPdenovo        6038  24   26     34     47      46791   498    11310   3009291  8982084  ?        48023   38    0  
 velvet**          705   45   60     84     584     142306  4046   33811   2852996  8982084  2898483  39096   854   12
 #scf stats
 .                 scfs  min  q1     q2     q3      max     mean   n50     sum            
 SOAPdenovo        482   100  270    1532   6719    58192   5849   18859   2819512  
 velvet            12    333  1111   27392  53828   142405  31488  78092   377866   # 2+ctg scaffolds        
  • Reference based(Saureus USA300)
 .                 ctgs  min     q1       q2       q3       max      mean    n50      sum      seqs     singl    0cvgSum snps  breaks
 maq**             1     2872913 2872913  2872913  2872913  2872913  2872913 2872913  2872913  8982084  2614519  2       3     0   

 Comments:
 * assembles in one piece
 * first & last bases in ref not covered
 * there is no read = ref.1-36 or ref.2872880-2872915
  • Reference based(Saureus MW2)
 .                ctgs  min  q1     q2     q3      max     mean   n50     sum      seqs     singl    0cvgSum snps  breaks
 maq              695   36   89     399    3304    77110   3914   17814   2720683  8982084  2801829  158246  4132  57

Illumina101 paired stats (cvg 78X; givenInsert=300 ; computerInsert=170)

  • DeNovo
 # ctg stats
 .                    ctgs       min     q1       q2      q3      max        mean      n50        sum     
 CA.bog               73         1716    14503    26431   52086   148524*    39043     58038*     2850157 
 SOAPdenovo           9382       32      32       52      63      85850      347       16726      3259522
 velvet               453        61      85       224     3279    137163     6297      36496      2852552 
 # scf stats
 .                    scf        min      q1      q2      q3      max        mean      n50        sum             
 CA.bog               67         1716     14869   32929   58038   148524*    42541     65383*     2850277
 SOAPdenovo           186        100      333     1528    17623   144079     15625     55558      2906207
 velvet               427        61       82      177     2982    137163     6685      37874      2854649
  • Comparative

Pseudomonas aeruginosa

  • PLoS article
 From 8,627,900 reads, each 33 nucleotides in length, we assembled the genome into one scaffold of 76 ordered contiguous sequences containing 6,290,005 nucleotides, 
 including one contig spanning 512,638 nucleotides, plus an additional 436 unordered contigs containing 416,897 nucleotides.

Read stats

 .                    elem       min    q1     q2     q3     max        mean       n50        sum        cvg     
 original             8627900    33     33     33     33     33         33.00      33         284720700  43.55X cvg    
 cor(quake)           7401074    30     33     33     33     33         32.75      33         242393133  37X    cvg

Assembly stats

  • DeNovo
                         elem       min    q1     q2     q3     max        mean       n50        sum            
 velvet(k=23)            7821       45     214    502    1108   16239      862.12     1541       6742621    !!! previous 
 velvet1.cor(k=21)**     5946       41     179    574    1472   20233      1129.77    2362       6717612    !!! new best
  • Comparative PA14
 .                       elem       min    q1     q2     q3     max        mean       n50        sum            
 AMOScmp.nucmer          1843       20     41     63     325    127984     3350.39    30660      6174765    !!! previous best : nucmer aligner
 AMOScmp.soap            1929       31     59     223    3395   79432      3182.93    13233      6139867    !!! new           : soap2  aligner
 AMOScmp.bowtie          1701       31     56     215    3535   79443      3610.23    15916      6141006    !!! new           : bowtie  aligner
  • Merged
 velvet1.cor(k=21)**     5946       41     179    574    1472   20233      1129.77    2362       6717612    !!! new best
 AMOScmp.nucmer          1843       20     41     63     325    127984     3350.39    30660      6174765    !!! previous best : nucmer aligner
 AMOScmp.nucmer-velvet   983        41     174    796    2859   309985     7390.19    53631      7264555

SRA projects

Whole genome based sequencing of a Escherichia fergusonii strain using 454 Technology.

  • SRP001132
  • 1 complete strain
  • Use 454 single/paired , titanium

E coli Whole Genome Sequencing on 454 and Illumina

Genome Sequencing of Mycobacterium tuberculosis PGG1

Plasmodium falciparum Whole Genome Assembly Development

Rhodobacter sphaeroides Sequencing on Illumina

  • 4 complete strains: NCBI search: "Rhodobacter sphaeroides"[Organism] AND pt_default[prop] AND seqstat_complete[PROP]
  • /fs/szdata//ncbi/genomes/Bacteria/Rhodobacter_sphaeroides_*/
  • chromosome lengths ~ 4Mbp
  • several plasmids
  • largest repeat : 5348 at 99.93%id; other repeats < 3k

Staphylococcus aureus Sequencing on Illumina

Whole Genome Sequencing of Streptomyces roseosporus NRRL 11379

Streptococcus pyogenes pathogenicity

Vibrio Choerae : PacBio long reads !!! =

Simulaterd reads

  • use MetaSim
  • MetaSim limitations:
    • Illumina reads (Empirical error model) always length==36
    • Exact reads : always unmated
  • get quality values & mate pairs:
 ~/bin/fasta2qual.pl prefix.seq > prefix.qual
 cat prefix.seq | grep "^>" | awk '{print $1}' | grep 1$ | p '/>(.+).1/; print "$1.1 $1.2\n";' > prefix.mates
 convert-fasta-to-v2.pl [ -454 ] -l prefix -mean 5000 -stddev 500 -s prefix.seq -q prefix.qual -m prefix.mates > prefix.frg

SRA

Download

  • SRRs (runs)
  cat SRR.txt | perl -ane 'next unless /(SRR...)/; print "wget ftp://ftp.ncbi.nih.gov/sra/sra-instant/reads/ByRun/litesra/SRR/$1/$F[0]/$F[0].lite.sra\n";'  => SRR001355.lite.sra
  cat SRR.txt | perl -ane 'next unless /(SRR...)/; print "wget ftp://ftp.ncbi.nih.gov/sra/sra-instant/reads/ByRun/sra/SRR/$1/$F[0]/$F[0].sra\n";'           => SRR001355.sra
  • SRXs (experiments)
  cat SRX.txt | perl -ane '/next unless (SRX...)/; system "wget -r ftp://ftp.ncbi.nih.gov/sra/sra-instant/reads/ByExp/litesra/SRX/$1/$F[0]/\n";'
  • SRPs (studies)
  cat SRP.txt | perl -ane '/next unless (SRP...)/; system "wget -r ftp://ftp.ncbi.nih.gov/sra/sra-instant/reads/ByStudy/litesra/SRX/$1/$F[0]/\n";'

Convert

 cat SRR.txt | perl -ane 'print "fastq-dump -A $F[0] -D $F[0].*sra\n";'   => SRR??????_[12].fastq
 cat SRR.txt | perl -ane 'print "sff-dump   -A $F[0] -D $F[0].*sra\n";'   => SRR??????.sff
  • sff-dump dump does not work on litesra

Download and convert

  • Example:
 ~/bin/SRRget.pl [-lite] SRR075011 | sh             # => SRR075011.fastq

Insert Size Estimate

 soap2-index ../1con/genome.1con
 touch ../1con/genome.1con.index
 cat SRR.txt | perl -ane 'print "soap2 -D ../1con/*.index -a $F[0]_1.fastq -b $F[0]_2.fastq -o $F[0]_12.mated.soap2 -2 $F[0]_12.single.soap2 -p 20\n";'
 cat SRR.txt | perl -ane 'print "cat $F[0]_12.*.soap2 | ~/bin/AMOS/soap2sameRef.pl -dist -max 10000 | getSummary.pl -i 1\n";'                               # => q2 ; add q2 vals as 2nd col in SRR.txt
 cat SRR.txt | perl -ane '$m=$F[1]*0.7; $x=$F[1]*1.3; print "soap2 -D ../1con/*.index -a $F[0]_1.fastq -b $F[0]_2.fastq -o $F[0]_12.mated.soap2 -2 $F[0]_12.single.soap2 -p 20 -m $m -x $x " ; print "-R" if($F[1]>1000); print "\n";'

454

Format

  • sff
  • linkers
 L454.flx          44     45.45   (palindrome)
 L454.titanium.fwd 42     30.95  
 L454.titanium.rev 42     30.95
  • fasta
  • fastq

Data sets

  • Sff
 /nfshomes/dpuiu/methanobrevibacter_smithii/Data/454/*sff          # single ; FLX ?
 /nfshomes/dpuiu/F_tularensis/SRA_FTP/*/*sff                       # single & paired ; GS20 & FLX
 /nfshomes/dpuiu/Brugia_malayi.new/Data/brugia-sequencing/*/*sff   # paired ; FLX & Ti
 /fs/szattic-asmg4/dpuiu/HTS/Escherichia_coli/Data/454/*fastq      # single from SRA !!!
 /fs/szattic-asmg4/dpuiu/HTS/Escherichia_coli/Data/454p/*fastq     # paired from SRA !!!

Converters

  • sff -> sff
 sffinfo -a in.sff | head -100 > out.acc
 sfffile -o out.sff -i out.acc in.sff
  • sff -> seq/qual (454 package)
 sffinfo -s prefix.sff > prefix.seq
 sffinfo -q prefix.sff > prefix.qual
  • sff -> frg2 (wgs package)
 sffToCA -insertsize mean std -linker [flx|titanium] -trim chop -libraryname prefix -output prefix.frg2 prefix.sff    # => prefix.frg2
 -trim chop: the read is chopped down to just the clear bases !!! should try it
  • fastq -> seq/qual -> frg2 (dpuiu & wgs)
 fastq2seq.pl  < prefix.fastq > prefix.seq
 fastq2qual.pl < prefix.fastq > prefix.qual
 convert-fasta-to-v2.pl -454 -l prefix -s prefix.seq -q prefix.qual > prefix.frg2
  • fastq -> frg2 (dpuiu & wgs)
 fastq2frg.sh prefix     # => prefix.frg2
  • seq/qual -> clean seq/qual -> frg2 (linker removal for 454p) (dpuiu)
 454p2seqqual.amos prefix    # => prefix.cseq,  prefix.cqual
 convert-fasta-to-v2.pl -454 -l prefix -s prefix.cseq -q prefix.cqual -l prefix -mean 3000 -stddev 300 -m prefix.mates > prefix.frg
 

See also

Illumina

Formats

  • Raw : the intensity values (int) and noise (nse) values.
  • Processed : the processed intensity values (sig2) and four-channel quality values (prb).
  • Base : the base calls (the quality value is gotten from the prb for the called base).

Converters

  • illumina <-> srf (illumina package)
 illumina2srf -o lane_no.srf BustardDir/s_lane_no_*_qseq.txt
 srf2illumina file.srf
  • split joined paired reads from SRA
 # seq/qual
 cat prefix.seq  | perl ~/bin/splitSeqMiddle.pl    > prefix.cseq
 cat prefix.qual | perl ~/bin/splitSeqMiddle.pl -q > prefix.cqual

 # fastq
 cat prefix.fastq | perl ~/bin/splitFastqMiddle.pl >  prefix.cfastq
 cat prefix.fastq | perl ~/bin/splitFastqMiddle.pl -f >  prefix.fwd.cfastq 
 cat prefix.fastq | perl ~/bin/splitFastqMiddle.pl -r >  prefix.rev.cfastq

SOLiD

Converters

  • SOLiD -> srf (SOLiD package)
 /fs/szdevel/dpuiu/solid2srf_v0.6.6/

Converters

SFR

Commands:

 srf2fasta
 srf2fastq
 srf_dump_all
 srf_extract_hash
 srf_extract_linear
 srf_filter
 srf_index_hash
 srf_info

FASTA/QUAL

  • seq/qual => frg2
 convert-fasta-to-v2.pl -l prefix -s prefix.seq -q prefix.qual > prefix.frg2
 
  • seq/qual => amos
 toAmos -m prefix.mates -s prefix.seq -q prefix.qual -o prefix.afg

FASTQ

 format                                   offset  qualityRanges
                                          0         1         2         3         4
                                          01234567890123456789012345678901234567890
 ===================================================================
 Sanger(cont. numbers)            33      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHI  !\"\#\$%&\'\(\)\*\+,-.\/0123456789:;<=>?\@ABCDEFGHI
 Illumina(cont. low cases)        64      @ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefgh

 CA frg packed                    48      0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWX
 ===================================================================


  • fastqToCA
 fastqToCA -insertsize 3000 300 -libraryname short -type sanger -fastq $PWD/short_1.fastq,$PWD/short_2.fastq > short_12.frg
 runCA -d . -p genome stopAfter=initialStoreBuilding short.frg 
 gatekeeper -dumpfrg -allreads -donotfixmates -format2 genome.gkpStore > genome.frg


  • fastq : input reads; id positions don't necessarily match; fwd read names end in 1, rev read names end in 2
 => fastq (_0: unmated; _[12]: mated) 
 fastq2seqs.pl < input_1.fastq | sed 's/1$//' > prefix_1.mate
 fastq2seqs.pl < input_2.fastq | sed 's/2$//' > prefix_2.mate
 intersect.pl prefix_1.mate prefix_2.mate     > prefix.mate

 cat prefix.mate | perl -ane 'print "$F[0]1 $F[0]2\n";' > prefix.mates

 difference.pl prefix_1.mate prefix.mate | perl -ane 'print "$F[0]1\n";' >  prefix.unmated
 difference.pl prefix_2.mate prefix.mate | perl -ane 'print "$F[0]2\n";' >> prefix.unmated

 extractfromfastqnames -i 0 -f prefix.unmated < prefix.fastq > prefix_0.fastq
 extractfromfastqnames -i 0 -f prefix.mates   < prefix.fastq > prefix_1.fastq
 extractfromfastqnames -i 1 -f prefix.mates   < prefix.fastq > prefix_2.fastq
 #or 
 fastq22fastq3.amos -D FWDSEQ=input_1.cor.txt -D REVSEQ=input_2.txt prefix
  • fastq2fastq
 maq sol2sanger illumina.fastq sanger.fastq
 ~/bin/fastq2afstq -in illumina -out sanger   < illumina.fastq > sanger.fastq
 ~/bin/fastq2afstq -in sanger   -out illumina < sanger.fastq   > illumina.fastq 
  • fastq => frg2
 fastq2seq.pl  < prefix.fastq > prefix.seq
 fastq2qual.pl < prefix.fastq > prefix.qual
 convert-fasta-to-v2.pl -l prefix -s prefix.seq -q prefix.qual > prefix.frg2

 ~/bin/fastq2frg.sh prefix

FRG

  • frg => frg2
 convert-v1-to-v2.pl [-v vector-clear-file] [-noobt] [-unmated] < prefix.frg > prefix.frg2

  • frg => amos
 toAmos -f prefix.frg -o prefix.afg
  • frg2 => frg
 gatekeeper -o prefix.gkpStore -T prefix.frg2
 gatekeeper -dumpfrg prefix.gkpStore > prefix.frg
  • frg => mates
 frg2mates.pl < prefix.frg > prefix.mates

 frg2acc.pl < prefix.frg > prefix.acc
 cat prefix.acc | ~/bin/difference1or2.pl -j1 1 -f prefix.mates > prefix.unmated
 extractfromfastqnames -i 0 -f prefix.unmated < prefix.fastq > prefix_0.fastq
 extractfromfastqnames -i 0 -f prefix.mates   < prefix.fastq > prefix_1.fastq
 extractfromfastqnames -i 1 -f prefix.mates   < prefix.fastq > prefix_2.fastq

AMOS

  • amos => frg
 amos2frg -i prefix.afg -o prefix.frg [-a accession] 
 removefromfrgmsg.pl prefix.frg ADT                      # in case convert-v1-to-v2.pl is run afterwards

  • amos => bank
 bank-transact -c -z -b prefix.bnk -m prefix.afg
 # for velvet assemblies
 grep "^>" Sequences | sed 's/>//' | awk '{print $1,$2}' > prefix.seqs
 
 bank2contig prefix.bnk/ | grep ^# | grep -v ^## | p '/(\d+)/; print $1,"\n";' | > prefix.assembled
 difference.pl -i 1 prefix.seqs prefix.assembled > prefix.singletons

TA (seq,qual,xml)

  • seq,qual,xml => frg
 tarchive2ca   -o prefix -c prefix.clr -l prefix.libinfo prefix.seq   # => prefix.frg

 tracedb-to-frg.pl (?)
  • seq,qual,xml => amos
 tarchive2amos -o prefix -c prefix.clr -l prefix.libinfo prefix.seq   # => prefix.afg

ACE

  • ace => amos
 toAmos -ace prefix.ace -m prefix.mates -o prefix.afg

Input processing

Quality assessment

  • Daniela's scripts
 cat prefix_1.fastq | ~/bin/getQualSummary.pl -type illumina > prefix_1.qual.summary
 cat prefix_2.fastq | ~/bin/getQualSummary.pl -type illumina > prefix_2.qual.summary

 cat ~/bin/plotQualSummary.gp | sed 's/prefix/Ecoli/g' >! plotQualSummary.gp
 gnuplot plotQualSummary.gp
 display Ecoli.qual.summary.png
  • Galaxity FASTX scripts
 ~/bin/fastx.sh prefix
 or
 fastx_quality_stats                     -i prefix.fastq -o prefix.stats
 fastq_quality_boxplot_graph.sh          -i prefix.stats -o prefix.quality_boxplot.png
 fastx_nucleotide_distribution_graph.sh  -i prefix.stats -o prefix.nucleotide_distribution_graph.png
 display *.png
 #the counts should be pretty uniform
 ls s*stats | p 'print "getSummary.pl -i 12 -t $F[0] -nh <$F[0]\n";' | sh | pretty >  A_count.stats
 ls s*stats | p 'print "getSummary.pl -i 13 -t $F[0] -nh <$F[0]\n";' | sh | pretty >  C_count.stats
 ls s*stats | p 'print "getSummary.pl -i 14 -t $F[0] -nh <$F[0]\n";' | sh | pretty >  G_count.stats
 ls s*stats | p 'print "getSummary.pl -i 15 -t $F[0] -nh <$F[0]\n";' | sh | pretty >  T_count.stats

Coverage assesment

soap2 ....
cat prefix*soap2 | ~/bin/AMOS/soap2posmap.pl | ~/bin/posmap2cvg.pl > prefix.cvg
plot "prefix.cvg" u 2:6 w l

Read trimming

  • Delete all reads that contain an N (or a quality of 0)
  • Compute Q20 & trim all reads to that length
  • Compute nucleotide bias. Trim 5',3' ends that show bias
  • Trim 5',3' ends

Adaptor removal

  • Using regular expressions (tested)
 ~/bin/cleanTitaniumAdaptorFromFastq.pl
 ~/bin/grep.pl -f ~/bin/titanium.fgrep 
 ~/bin/cleanAdaptorFastq.pl -tita -min 32

Read correction

  • quake
  echo prefix_1.fastq prefix_2.fastq  > prefix.ls
  quake.py -f prefix.ls -k 18 -p 16

or

 cat prefix*fastq | count-qmers -k 18 > prefix.ls.qcts
 gzip prefix.ls.qcts
 cov_model.py prefix.ls.qcts  | tail -1  | p 'print $F[1]' > prefix.cutoff                            # takes pretty long to run
 cov_model.py 18mers.qcts >& /dev/null
 tail -1 cutoff.txt | perl -ane 'print $F[0]' > prefix.cutoff
 correct -f prefix.ls -k 18 -c `cat prefix.cutoff` -m prefix.ls.qcts -p 4
  • Aleksey's
 set SIZE=100000000 # 100M
 jellyfish count -s 1000000 -m 18 --both-strands -t 16 -o frag.k18.jf frag_?.*fastq
 jellyfish merge frag.k18.jf_* -o frag.k18.jf
 jellyfish histo frag.k18.jf | head -20  => bottom=cuttof
 correct -f prefix.ls -k 18 -c cutoff -m 18mers.qcts -p 4
  • SOAP correction
 ls -1 prefix_1.fastq prefix_2.fastq  > prefix.ls
 ~/szdevel/correction/KmerFreq  -i prefix.ls -o prefix.cor      -s 18      
 ~/szdevel/correction/Corrector -i prefix.ls -r prefix.cor.freq -s 18 -t 16
 Issue: too many reads are discarded
  • hybrid-shrec : multiple platform correction
 http://www.cs.helsinki.fi/u/lmsalmel/hybrid-shrec/

Lucy

 lucy -debug prefix.lucy.info prefix.seq prefix.qual 
 cat prefix.lucy.info | awk '{print $1,$3,$4}' > prefix.lucy.clr

 ~/bin/clrFasta.pl -f prefix.lucy.clr    < prefix.seq  > prefix.lucy.seq
 ~/bin/clrFasta.pl -f prefix.lucy.clr -q < prefix.qual > prefix.lucy.qual

CA

  • 454 reads
 runCA -stopAfter OBT ...

 gatekeeper -dumpfragments                   -tabular asm.gkpStore | p 'print $F[-3],"\n" unless($F[6]);'        | getSummary.pl -t ORIG
 gatekeeper -dumpfragments -clear CLR        -tabular asm.gkpStore | p 'print $F[-1]-$F[-2],"\n" unless($F[6]);' | getSummary.pl -t CLR
 gatekeeper -dumpfragments -clear OBTINITIAL -tabular asm.gkpStore | p 'print $F[-1]-$F[-2],"\n" unless($F[6]);' | getSummary.pl -t OBTINITIAL
 gatekeeper -dumpfragments -clear OBTCHIMERA -tabular asm.gkpStore | p 'print $F[-1]-$F[-2],"\n" unless($F[6]);' | getSummary.pl -t OBTCHIMERA
 gatekeeper -dumpfragments -clear LATEST      -tabular asm.gkpStore | p 'print $F[-1]-$F[-2],"\n" unless($F[6]);' | getSummary.pl -t LATEST

Simulators

  • Maq: max read len can be recompiled; must be trained on a data set;
 ~/db/Illumina.simutrain.dat : trained on 75 bp Illumina "high qual" reads (q2>30 for all pos)
 maq simutrain train.dat train.fastq
 maq simulate     -d libMea -s libStd -r 0  -N noMates -1 read1Len -2 read2Len read1Out read2Out ref.fasta  train.dat
  • Samtool
 wgsim -e 0       -d libMea -s libStd -r 0 -N noReads -1 read1Len -2 read2Len ref.fasta read1.fastq read2.fastq -C   # error free reads
 wgsim -e readErr -d libMea -s libStd -r 0 -N noReads -1 read1Len -2 read2Len ref.fasta read1.fastq read2.fastq -C  # error in reads
  • Others:
 dwgsim
 simseq Used by Assemblathon !!!

Links