Trace formatting

From Cbcb
Revision as of 21:56, 8 December 2008 by Dpuiu (talk | contribs) (→‎SOCS)
Jump to navigation Jump to search

Articles

Throughput, Short-Read Technologies]

Technologies

Latest Technology Summary 

 Technology            454                       Illumina                              Solid

                       seq-by-synthesis            seq-by-synthesis                        ABI
 Company               454(Roche)                  Illumina
 Location              Brandford,CT                SanDiego,CA          
 Latest                GS FLX, Titanium reagents   Genome Analyzer II                      SOLID 3

 Throughput            500M/run                    1G/run                                  20G/run
 RunTime               10hr                        3days
 ReadLen               500bp                       36                                      35
 InsertLen             3K                          100-200bp                               600-10K 

 Accuracy                                                                                  99.94%
 Q20(99%accuracy)      400bp                       34bp
 Cost                                              $3K/run                                 60K/3G                             
                                                   $400/4M bacterial genome(25-30X)
 Problems              homopolimers


Sanger

454

Anomalies: 

 * homopolymer lengths can be shorter than real
 * substitutions less likely than in traditional methodssingle base insertions
 * carry forward events usually near but not adjacent to homopolymers

GS20 

 * 1.6M total wells
 * 450K detactable wells
 * 200K usable wells

 Accuracy:
 * published per-base accuracy of a Roche GS20 is only 96%.
 * Mitch Sogin paper
   * 99.5% accuracy rate in unassembled sequences
   * identified several factors that can be used to remove a small percentage of low-quality reads, improving the accuracy to 99.75% or better => better quality than Sanger sequencing
   * The error rate, defined as the number of errors (miscalled bases plus inserted and deleted bases) divided by the total number of expected bases, was 0.49%
  * 36% insertions, 27% delitions, 21% N's, 16% substitutions
  * A to G and T to C, were more frequent than other mismatches
  * reverse transitions, G to A and C to T, were not that frequent 
  * Nearly 70% of the homopolymer extensions were A/T
  * errors were evenly distributed along the length of the reference sequences, they were not evenly distributed

among reads: 82% had no errors, 93% had no more than a single error, and 96% had no more than 2 errors. 

  * A small number of reads, fewer than 2%, contained a disproportionate number of errors that account for nearly 50% of the miscalls for the entire dataset  
  * Avg quality is 25; in homopolymers can drop as low as 5
  * Reads much longer than avg length had more errors
  * strong correlation between the presence of ambiguous base calls and other errors in a read
  * The presence of even a single ambiguous base in a read correlates strongly with the presence of other errors 
  * Primer errors also correlated with errors

GS FLX

GS FLX with Titanium reagents 

 * up to 500M/run
 * reads up to 500bp

Get info from .sff files: 

 $ sffinfo -h
 Usage:  sffinfo [options...] [- | sfffile] [accno...]
 Options:
      -a or -accno      Output just the accessions
      -s or -seq      Output just the sequences
      -q or -qual     Output just the quality scores
      -f or -flow     Output just the flowgrams
      -t or -tab      Output the seq/qual/flow as tab-delimited lines
      -n or -notrim   Output the untrimmed sequence or quality scores
      -m or -mft      Output the manifest text

un-paired reads

paired ends

Features: 

 * approximately 84-nucleotide DNA fragments 
 * have a ~ 44-mer linker sequence in the middle 
 * flanked by a ~ 20-mer sequence on each side. 
 * The two flanking 20-mers are segments of DNA that were originally located approximately 2.5 (3?) kb apart in the genome of interest.  
 * The ordering and orienting of contigs generates scaffolds which provide a high-quality draft sequence of the genome.

 Linker(palindrome) : GTTGGAACCGAAAGGGTTTGAATTCAAACCCTTTCGGTTCCAAC
 Check for linker   : sffinfo -s *.sff | ~/bin/fasta2tab.pl | grep GTTGGAACCGAAAGGGTTTGAATTCAAACCCTTTCGGTTCCAAC
 
 12345678901234567890123456789012345678901234
 GTTGGAACCGAAAGGGTTTGAATTCAAACCCTTTCGGTTCCAAC 

 GTTGGAACCGA
 AAGGGTTTGAA
 TTCAAACCCTT
 TCGGTTCCAAC

Anomalies: 

 * the linker can appear (tandem,completely/partially) more than once
 * some reads end up in linker (partial)
 * some reads don't contain the linker at all
 * some reads are cloning vector

Links: 

 1_paired_end.pdf

File location: 

 /fs/szdata/454p/

Illumina

  • Sequencing by Synthesis
  • Platforms:
 * Genome Analyzer (GA)
 * Genome Analyzer II : faster, higher tput
 * Future: 10GB/run  50bp reads
 * Future: 20GB/run 100bp reads

Data sets: 

 Strep suis Solexa data set for download at Sanger
 Staphylococcus aureus strain MW2 (edena paper)
 NCBI Solexa example data set
 Pseudomonas aeruginosa
 Pseudomonas syringae
 NCBI SRA

Applications: 

 * Gene Expression
 * ChIPSeq (hight throughput)
 * Re-sequencing
 * mRNA sequencing

Software: 

 Staden & Io_lib
 * IO_LIB package /fs/sz-user-supported/common/packages/io_lib-1.11-x86_64/bin/
 * STADEN package /fs/sz-user-supported/common/packages/staden-src-1-7-0/distrib/unix-rel-1-7-0/linux-bin
 
 MAQ Sanger assembler
 FASTQ sequence format

Illumina 1G : 

 * ~40 Million DNA sequencing reactions
 * about 36 hours for a run
 * each sequence is up to 36 bases long
 * insert len=~200bp

Illumina Genome Analyzer II: 

 * up to 51 bp
 * mate-pairs: opposite directions, slight overlap (insert size is less than 200bp "advertised")
 * on the SRA mate-pairs are joined; when downloaded only one read is shown. What about the mate pair?

SRA: set of 4 files 

 *_seq.txt  : lane,run, well(x,y) sequence
 *_prb.txt  : max quality from each group of 4 values is taken as quality
 *_sig2.txt : lane,run, well(x,y); max signal from each group of 4 values corresponds to max quality
 *_qhg.txt  : lane,run, well(x,y); some encoded info?

 # *_seq.txt 
 5       1       1269    1795    AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA  
 # _prb.txt 
 40  -40  -40  -40       40  -40  -40  -40  ...
 # _sig2.txt <==
 5       1       1269    1795    2594.0 2367.0  -10.0  -96.0 ...

Qualities: 

 Range : -5..40
 Avg   : ~25, depending on the data set

Fastq format

Maq help

Example: 

 1 lane of Solexa reads: 10,959 READS; all are 36 bp
 $ /fs/sz-user-supported/common/packages/io_lib-x86_64/bin/solexa2srf s_8_0100_seq.txt  ; mv traces.srf  s_8_0100.srf
 $ /fs/sz-user-supported/common/packages/io_lib-x86_64/bin/srf2fastq s_8_0100.srf > s_8_0100.fastq

   @s_8_100_293_551
   CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCACC
   +
   IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII
   @s_8_100_35_698
   TATATGATTGACAATATAAAAATATGAGTATAAAAT
   +
   IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII4/:I
   @s_8_100_880_947
   TTATTATCTTTATTGACGTACCTCTAGAAGACCCAA
   +
   IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII;>1
   ...

 Edge effect: 
 N's have quality -14

 $ cat s_8_0100_seq.txt | sort -nk3 -nk4 
 8       100     0       37      ......AT.AT...TAATCAATA..GA.GAAG....
 ...
 8       100     1003    959     AGTC.......T.C.........GT.........AA

 $ more traces.qual
 ...
 >s_8_100_0_37
 -14 -14 -14 -14 -14 -14 25 13 -14 25 25 -14 -14 -14 25 25 25 25 22 25 25 25 25 -14 -14 25 25 -14 25 -11 25 14 -14 -14 -14 -14 
 ...
 >s_8_100_1003_959
 25 25 25 25 -14 -14 -14 -14 -14 -14 -14 25 -14 25 -14 -14 -14 -14 -14 -14 -14 -14 -14 25 -10 -14 -14 -14 -14 -14 -14 -14 -14 -14 8 25
 ...

 # bioperl script to convrt seq formats
 $ seqconvert.PLS --from fastq --to fasta < s_8_0100.fastq
 
 # get fastq qualities
 $ more *fastq | grep -A 1 "^+" | grep -v ^+ | grep -v -- ^-- | perl -ane '@F=split //,$F[0]; foreach (@F) { $n=ord($_)-33; print $n," ";} print "\n";'

 # convert Solexa format (maq fq_all2std.pl script)
 $ fq_all2std.pl seqprb2std s_5_0001_seq.txt s_5_0001_prb.txt > s_5_001.fastq
 $ fq_all2std.pl fq2fa s_5_001.fastq > s_5_001.seq

SOLiD

Example: 

 Ecoli_F3.csfasta
 >600_50_31_F3
 T2222002113300322132112231
 >600_50_63_F3
 T2330133212130133221033110

 Ecoli_F3_QV.qual
 >600_50_31_F3
 15 20 14 11 25 20 17 21 16 9 15 12 21 8 2 10 15 5 3 5 10 6 2 4 4
 >600_50_63_F3
 5 13 9 23 5 9 8 4 6 4 5 4 7 6 10 7 7 5 13 11 5 8 2 7 6

 Ecoli_R3.csfasta
 >600_51_85_R3
 G0331332123123330101312331
 >600_51_178_R3
 G1111033111110111101111111

 Ecoli_R3_QV.qual
 >600_51_85_R3
 10 13 16 15 11 17 6 13 10 9 15 8 13 10 12 11 8 5 3 6 12 8 11 6 14
 >600_51_178_R3
 2 2 2 5 8 2 2 2 2 3 2 3 2 3 7 4 3 4 5 4 2 2 5 6 17
  • low error rate (higher accuracy than Illumina)
  • 2008: 4G run, read_len=35bp; insert=3Kbp (old)
  • 2009: 9G run, read_len=50bp;
  • SOLiD™ 3 System generates (Oct 1 2008)
    • over 20 gigabases
    • mate-paired libraries with insert sizes ranging from 600 bp up to 10 kbp
    • human genome for less than $60,000.
  • uniform bases quality
  • accuracy greater than 99.94%
  • because of double base interogation & high cvg, qualities can be "discarded"

Alignment matrix 

   A C G T
 A 0 1 2 3
 C 1 0 3 2
 G 2 3 0 1
 T 3 2 1 0

Examples: 

  AA is encoded as 0
  CG is encoded as 3
  AACG is encoded as 0 1 3

Features of Color space: 

 * Color space data are self-complementary

   Example:
       Base        A G C T C G T C G T G C A G
       Color space   2 3 2 2 3 1 2 3 1 1 3 1 2
   
       Complemented
       Base        T C G A G C A G C A C G T C
       Color space   2 3 2 2 3 1 2 3 1 1 3 1 2

 * Two-Base Encoding and Error Recognition
   1 change: measuring error 
   multiple changes starting at a certain point: SNP

   Example:
      Reference 2 3 2 2 3 1 2 3 1 1 3 1 2
      Observed  2 3 2 2 0 1 2 3 1 1 3 1 2

Data Sets:

Pos-vs-quality.png

Helicos

Pacific Biosystems

Visigen

Download

Genbank

  • Bioperl scripts:
 bp_fetch.pl net::genbank:NC_005810.1 > NC_005810.1
 bp_fetch.pl net::genbank:NC_005810 > NC_005810
 bp_fetch.pl net::genbank:45439865 > 45439865

TA

SRA

Format

TA

  • Sanger:
 tarchive2amos -o Ba Ba.seq                                              # TA FTP
 tarchive2amos -o Ba -tracedir traces/                                   # TA querytrace_db 
 tarchive2amos -o Ba -assembly assembly/ASSEMBLY.xml -tracedir traces/   # AA

SRA

  • Solexa mated:
 seq2amos.pl -n solexap -m 100 -s 20 -fs solexa_f.fasta  -rs solexa_f.fasta  > solexap.afg
 seq2amos.pl -n solexap -m 100 -s 20 -fs solexa_f.fasta -fq solexa_f.qual -rs solexa_r.fasta -rq solexa_r.qual > solexap.afg
 seq2amos.pl -n solexap -m 100 -s 20 -fs solexa_f*.fasta -rs solexa_r*.fasta > solexap.afg
  • Solexa unmated:
 seq2amos.pl -n solexa               -fs solexa.fasta                        > solexa.afg
  • 454 mated:
 seq2amos.pl -n 454p    -m 3000 -s 300 -fs 454.seq                           > 454p.afg
  • 454 unmated:
 seq2amos.pl -n 454                    -fs 454.seq                           > 454.afg

Convestion

  • Readseq
 ~/bin//readseq.sh -f Fasta -o prefix.fasta prefix.embl
  • Bioperl
 bp_sreformat.pl -i prefix.embl -o prefix.fasta -if EMBL -of Fasta
  • AMOS:
 amos2frg [-i infile] [-o outfile] 
 amos2sq [-i] infile [-o outprefix] =>  outprefix.seq outprefix.qual

Read Mapping Software

BFAST

  • need to e-mail to author to get the code

BLAT

 blat -noHead -t=dna  -q=dna  -tileSize=10 -stepSize=3 Pa.1con    Pa.seq    Pa.blat

MAQ *

 SOLEXA
 maq.pl easyrun -d . ref.1con reads.fastq

 SOLID
 solid2fastq.pl reads_ shortname
 maq fastq2bfq shortname.fastq shortname.bfq
 maq fasta2csfa ref.fasta > ref.csfa
 maq fasta2bfa ref.csfa ref.csbfa
 maq fasta2bfa ref.fasta ref.bfa
 maq map -c aln.cs.map ref.csbfa shortname.bfq 2> aln.log
 maq csmap2nt aln.nt.map ref.bfa aln.cs.map
 maq assemble cns.cns ref.bfa aln.nt.map 2> cns.log

RMAP

  • RMAP : designed for Illumina-Solexa
  • Command: rmap
 rmap         -m 3 -w 33                            -c Pa.1con    Pa.seq -o Pa.rmap

SHRiMP

  • Web site
  • Commands: rmapper-cs , rmapper-ls, ...

SeqMap

  • SeqMap developed at Stanford
  • allows up to five mixed substitutions and inserted/deleted nucleotides in the mapping
  • allows sequences to contain N’s, and to have unequal lengths
 ./seqmap
 Usage: seqmap <number of mismatches> <probe FASTA file name> <transcript FASTA file name> <output file name> [options]
 
 Parameters:
 <number of mismatches>                          maximum edit distance allowed
 <probe FASTA file name>                         probe/tag/read sequences
 <transcript FASTA file name>                    reference sequences
 <output file name>                              name of the output file
 ...

SHORE

SOAP *

 soap         -v 5                                  -d Pa.1con -a Pa.seq -o Pa.soap

SOCS

 socs socs.pref
 more socs.pref
 Req.fa
 Seq_F3.csfasta
 Seq_F3_QV.qual
 out_prefix
 2
 1000
 2
 false
 true
 0

SOLiD

SSAHA

  • Web site(Sanger)
  • Focused on exact, nearly exact matches
  • Does not find all the exact matches???
  • Example: Solexa 33bp ~30% of reads are not found

ZOOM

Genome Resequencing

Links

Data

Solexa

 Accession       #Runs   Instrument                      Center  Study                          [Individual]
 SRA000303       41      Solexa 1G Genome Analyzer       BI      1000Genomes Project Pilot 2     NA12878
 SRA000304       49      Solexa 1G Genome Analyzer       BI      1000Genomes Project Pilot 2     NA12891
 SRA000305       56      Solexa 1G Genome Analyzer       BI      1000Genomes Project Pilot 2     NA12892
 SRA000307       1       Solexa 1G Genome Analyzer       SC      1000Genomes Project Pilot 1     NA10851
 SRA000308       2       Solexa 1G Genome Analyzer       SC      1000Genomes Project Pilot 1     NA11993
 SRA000309       3       Solexa 1G Genome Analyzer       SC      1000Genomes Project Pilot 1     NA11995
 SRA000310       1       Solexa 1G Genome Analyzer       SC      1000Genomes Project Pilot 1     NA12006
 SRA000311       1       Solexa 1G Genome Analyzer       SC      1000Genomes Project Pilot 1     NA12044
 SRA000312       2       Solexa 1G Genome Analyzer       SC      1000Genomes Project Pilot 1     NA12156
 SRA000313       1       Solexa 1G Genome Analyzer       SC      1000Genomes Project Pilot 1     NA12414
 SRA000314       1       Solexa 1G Genome Analyzer       SC      1000Genomes Project Pilot 1     NA12776
 SRA000315       1       Solexa 1G Genome Analyzer       SC      1000Genomes Project Pilot 1     NA12828
 SRA000316       12      Solexa 1G Genome Analyzer       SC      1000Genomes Project Pilot 2     NA12878
 SRA000317       8       Solexa 1G Genome Analyzer       SC      1000Genomes Project Pilot 2     NA12891
 SRA000318       14      Solexa 1G Genome Analyzer       SC      1000Genomes Project Pilot 2     NA12892
 SRA000319       1       Solexa 1G Genome Analyzer       SC      1000Genomes Project Pilot 1     NA12004

June 14th 2008: Sept 19th 2008 

 SRA001100       23      Illumina Genome Analyzer        BGI     1000Genomes Project Pilot 2     NA19240
 ...
 SRA002029       1       Illumina Genome Analyzer II     WUGSC   1000Genomes Project Pilot 2     NA19239

 /fs/szdata/Solexa/1000genomes
  • Example SRR001113.seq :
 7,058,926 47 bp sequences
 2,402,398 contain at least 1 '.'

454

  • 1000 Genomes

June 14th 2008 

 Accession       #Runs   Instrument      Center  Study                           [Individual]
 SRA000302       121     454 GS FLX      BCM     1000Genomes Project Pilot 2     NA12878
 SRA001032       2       454 GS FLX      BCM     1000Genomes Project Pilot 2     NA12878
 SRA001036       1       454 GS FLX      BCM     1000Genomes Project Pilot 1     NA12812
 SRA001094       1       454 GS FLX      BCM     1000Genomes Project Pilot 2     NA12878

June 14th 2008: Sept 19th 2008 

 SRA001037       2       454 GS FLX      BCM     1000Genomes Project Pilot 1     NA12812
 ...
 SRA001819       1       454 GS FLX      BCM     1000Genomes Project Pilot 2     NA12878

Refseq

  • /fs/szdata/genomes/human_ncbi_build36/ NCBI build36.1 May 2006 (Current build is 36.3 March 2008)
  • /fs/szdata/genomes/human_celera_2001_Orig/

Alignments

Whole genomes alignments

Retrieved from "https://wiki.umiacs.umd.edu/cbcb/index.php?title=Trace_formatting&oldid=4109"