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GBS Bioinformatics Pipeline(s) Overview

Published bySylvia Dennis Modified over 9 years ago

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Presentation on theme: "GBS Bioinformatics Pipeline(s) Overview"— Presentation transcript:

1 GBS Bioinformatics Pipeline(s) Overview
Getting from sequence files to genotypes. Pipeline Coding: Ed Buckler Jeff Glaubitz James Harriman Presentation: Terry Casstevens With supporting information from the coders.

2 Three Pipelines Discovery Pipeline Production Pipeline UNEAK Pipeline
Requires a reference genome Multiple steps to get to genotypes Hands on tutorial is based on this pipeline Production Pipeline Uses information from Discovery Pipeline One step from sequence to genotypes UNEAK Pipeline For species without a reference genome Fei Lu will present this tomorrow at 9:30

3 Vocabulary Sequence File Taxa GBS Bar Code Key File GBS Tag Plugin
Text file containing DNA sequence reads and supplemental information from the Illumina Platform. Taxa An individual sample GBS Bar Code A short known sequence of DNA used to assign a GBS Tag to its original Taxa Key File Text file used to assign a GBS Bar Code to a Taxa GBS Tag DNA sequence consisting of a cut site remnant and additional sequence. Plugin Tassel pipeline module that performs specific task

4 GBS Discovery Pipeline
Tag Counts SNP Caller Genotypes Tags by Taxa Sequence TOPM

5 GBS Discovery Pipeline
Tag Counts SNP Caller Genotypes Tags by Taxa Sequence TOPM

6 Raw Sequence (Qseq) HWI-ST GTCGATTCTGCTGACTTCATGGCTTCTGTTGACGACGATGTGGAACGAGCTGTTGTTGAAACTGATGAGGTTGCTGAGATCGGAAGAGCGGTTCAGCAGG HWI-ST GAGAATCAGCTTTTCCAACACCTTGAGTTTGAGTATGCGATGACAGTTACTCTTACTGTCCATTGTCAGCATTGCCAGAGCTTGACCAGCTGAGATCGGA HWI-ST ATGTACTGCACCGTTGCAAGCGAGCACCACCAAGCGGCGGTATGCACTTTGCAATATGTAGCTAGAATAGGATTTTCAGGTGATTAGGAGCGTAAAAAAG HWI-ST CCAGCTCAGCCTGCATTCTTTCAAAAACTTCCAATGCCTCTCTTGGCCTAGCATTTTGGGCATACCCTGTGACCATTGCTGTCCATGCCACCATATCCTT HWI-ST GATTTTACTGCACATCGGTCTTGTCACACCAGCTATACCTGTAGAGTTGCCTTCCACAGTTGTAGAGATCGGAAGAGCGGTTCAGCGGGACTGCCGAGAA HWI-ST TCACCCAGCATCACGCCCCTTCACATCCAGTAAAACCCCTGAATGATGTGCTGTCACTGTTTGATATACAGTTGTTAACGTGAGGACGGGCTTTGAAGGA HWI-ST CTTGACTGCCACCATGAATATGTGTTCCAAGTGCCACAAGGACTTGGCCCTGAAGCAAGAACAAGCCAAACTTGCAGAGATCGGAAGAGCGGTTCAGCAG HWI-ST CCACAACTGCTCCATCTTTTCCATGAGACATTGCTCCCGCCATTGCACCCTTGGCATCAGCAGAGATCGGAAGAGCGGTTCAGCAGGAATGCCGAGACCG HWI-ST GTATTCTGCACACGAATCAGCTGAGACACCAATTGGGCATGAATCAAATGGCGCCATTGCCGGGGATCGAACCCCGAATCAAATGGTGCCATTGCCACTG HWI-ST AATATGCCAGCAGTTAAGAGAGTTCAAGATCCAGGGCTCATATTCAGTCACCTATATCAATTTCGAAATGGATTTCCAGGGTTTTAAGAGCCTAACAAAG HWI-ST CTCCCTGCGGGTGCGCGCGACCCATCTTCAGTTGGAGCGTCTATCGGCGTTGCTGAGATCGGAAGAGCGGTTCAGCAGGAATGCCGAGACCGATCTCGTA HWI-ST TGGTACGTCTGCGGAATGGCGTTTTTTATGCCTTAGTGGTTCGCAGAGCATTTGGCAGCTGAGATGGGAAGAGCGGTTCAGCAGGAATGCCGAGACCGAT HWI-ST GGACCTACTGCCCAAGAACGGCTCACCCATCATCCGCTTTCTTCACCTTCCGTCTTCTTTGGCTGAGATCGGAAGAGCGGTTCAGCAGGAATGCCGAGAC HWI-ST GAGAATCAGCGTGTACGGGGCACGGGGTGACTGCTGTTGCGTGCGAGGGCTGAGATCGGAAGAGCGGTTCAGCAGGAGTGCCGAGACCGATCTCGTATGC HWI-ST TTCTCCAGCCGCATGGGCCGGAGACCAGAGAGGCCTCCCCAGGATTTGCACGATAGACCACGACTTATGGACGATTGGGAAGCCCTTGTTGGAAGGAAAT HWI-ST GCGTCAGCAAATGCCCCAACAGCCAAGTCAGCAATTGCCTCAGCAACTTGGGCCACAAACACCACAGCTGAGATCGGAAGAGCGGTTCAGCAGGAATGCC HWI-ST TAGGCCATCAGCTGACTTCCCGGGTGTGGAGAAAAGAGGGCCCCTCACTTCTCTCAAGTGCTGAGATCGGAAGAGCGGTTCAGCAGGAATGCGGAGACCG HWI-ST GGACCTACTGCCGGCGGGACGAAAGCGGTTGTTGAATGATGGGGGTCACTAGGCCTTCCAGGGCCTTTAAGCGCGCGCTGAGATCGGAAGAGGGGTTCAG HWI-ST CTCCCTGTTGAAGCATGTGCAAAAGAGCTTGTTCTCGGCCTTCTTCAAGCCATTCTCTTGGCAGACGGCTTTGCCTAGAAGTTTCGCCCCATCACCCTTG HWI-ST CGCCTTATCTGCCCTCGCCGGTCATGGGGAGTGGTGCCCCTACCTCGGACAAGACAGATGCAGAGATCGGAAGAGCGGTTCAGCAGGAATGCCGAGACCG

7 Raw Sequence (Qseq) HWI-ST GTCGATTCTGCTGACTTCATGGCTTCTGTTGACGACGATGTGGAACGAGCTGTTGTTGAAACTGATGAGGTTGCTGAGATCGGAAGAGCGGTTCAGCAGG HWI-ST GAGAATCAGCTTTTCCAACACCTTGAGTTTGAGTATGCGATGACAGTTACTCTTACTGTCCATTGTCAGCATTGCCAGAGCTTGACCAGCTGAGATCGGA HWI-ST ATGTACTGCACCGTTGCAAGCGAGCACCACCAAGCGGCGGTATGCACTTTGCAATATGTAGCTAGAATAGGATTTTCAGGTGATTAGGAGCGTAAAAAAG HWI-ST CCAGCTCAGCCTGCATTCTTTCAAAAACTTCCAATGCCTCTCTTGGCCTAGCATTTTGGGCATACCCTGTGACCATTGCTGTCCATGCCACCATATCCTT HWI-ST GATTTTACTGCACATCGGTCTTGTCACACCAGCTATACCTGTAGAGTTGCCTTCCACAGTTGTAGAGATCGGAAGAGCGGTTCAGCGGGACTGCCGAGAA HWI-ST TCACCCAGCATCACGCCCCTTCACATCCAGTAAAACCCCTGAATGATGTGCTGTCACTGTTTGATATACAGTTGTTAACGTGAGGACGGGCTTTGAAGGA HWI-ST CTTGACTGCCACCATGAATATGTGTTCCAAGTGCCACAAGGACTTGGCCCTGAAGCAAGAACAAGCCAAACTTGCAGAGATCGGAAGAGCGGTTCAGCAG HWI-ST CCACAACTGCTCCATCTTTTCCATGAGACATTGCTCCCGCCATTGCACCCTTGGCATCAGCAGAGATCGGAAGAGCGGTTCAGCAGGAATGCCGAGACCG HWI-ST GTATTCTGCACACGAATCAGCTGAGACACCAATTGGGCATGAATCAAATGGCGCCATTGCCGGGGATCGAACCCCGAATCAAATGGTGCCATTGCCACTG HWI-ST AATATGCCAGCAGTTAAGAGAGTTCAAGATCCAGGGCTCATATTCAGTCACCTATATCAATTTCGAAATGGATTTCCAGGGTTTTAAGAGCCTAACAAAG HWI-ST CTCCCTGCGGGTGCGCGCGACCCATCTTCAGTTGGAGCGTCTATCGGCGTTGCTGAGATCGGAAGAGCGGTTCAGCAGGAATGCCGAGACCGATCTCGTA HWI-ST TGGTACGTCTGCGGAATGGCGTTTTTTATGCCTTAGTGGTTCGCAGAGCATTTGGCAGCTGAGATGGGAAGAGCGGTTCAGCAGGAATGCCGAGACCGAT HWI-ST GGACCTACTGCCCAAGAACGGCTCACCCATCATCCGCTTTCTTCACCTTCCGTCTTCTTTGGCTGAGATCGGAAGAGCGGTTCAGCAGGAATGCCGAGAC HWI-ST GAGAATCAGCGTGTACGGGGCACGGGGTGACTGCTGTTGCGTGCGAGGGCTGAGATCGGAAGAGCGGTTCAGCAGGAGTGCCGAGACCGATCTCGTATGC HWI-ST TTCTCCAGCCGCATGGGCCGGAGACCAGAGAGGCCTCCCCAGGATTTGCACGATAGACCACGACTTATGGACGATTGGGAAGCCCTTGTTGGAAGGAAAT HWI-ST GCGTCAGCAAATGCCCCAACAGCCAAGTCAGCAATTGCCTCAGCAACTTGGGCCACAAACACCACAGCTGAGATCGGAAGAGCGGTTCAGCAGGAATGCC HWI-ST TAGGCCATCAGCTGACTTCCCGGGTGTGGAGAAAAGAGGGCCCCTCACTTCTCTCAAGTGCTGAGATCGGAAGAGCGGTTCAGCAGGAATGCGGAGACCG HWI-ST GGACCTACTGCCGGCGGGACGAAAGCGGTTGTTGAATGATGGGGGTCACTAGGCCTTCCAGGGCCTTTAAGCGCGCGCTGAGATCGGAAGAGGGGTTCAG HWI-ST CTCCCTGTTGAAGCATGTGCAAAAGAGCTTGTTCTCGGCCTTCTTCAAGCCATTCTCTTGGCAGACGGCTTTGCCTAGAAGTTTCGCCCCATCACCCTTG HWI-ST CGCCTTATCTGCCCTCGCCGGTCATGGGGAGTGGTGCCCCTACCTCGGACAAGACAGATGCAGAGATCGGAAGAGCGGTTCAGCAGGAATGCCGAGACCG

8 Key File

9 GBS Tags Fragment from GBS library:
Insert Barcode adapter Cut site Common adapter ‘Good’ reads: (only the first 64 bases after the barcode are kept) typical read: Insert (first 64 bases) Barcode Cut site short fragment: Insert (<64bp) Barcode Cut site Common adapter chimera or partial digestion: Insert (<64bp) Cut site 2nd Insert Barcode

10 GBS Tags Fragment from GBS library:
Insert Barcode adapter Cut site Common adapter ‘Good’ reads: (only the first 64 bases after the barcode are kept) typical read: Insert (first 64 bases) Barcode Cut site short fragment: Barcode Cut site Insert (<64bp) Cut site chimera or partial digestion: Barcode Cut site Insert (<64bp) Cut site

11 GBS Tags Fragment from GBS library:
Insert Barcode adapter Cut site Common adapter ‘Good’ reads: (only the first 64 bases after the barcode are kept) typical read: Insert (first 64 bases) Barcode Cut site short fragment: Barcode Cut site Insert (<64bp) Cut site chimera or partial digestion: Barcode Cut site Insert (<64bp) Cut site Rejected reads: Barcode Cut site Common adapter adapter dimer Not matching barcode and cut site remnant Contains N in first 64 bases after the barcode

12 GBS Discovery Pipeline
Tag Counts SNP Caller Genotypes Tags by Taxa Sequence TOPM

13 Tag Counts With information from the key file, each sequence file is processed, tags are identified and counted. If a tag is shorter than 64 bases it is padded. The tags and counts are put into a tag count file for each sequence file. QseqToTagCountsPlugin / FastqToTagCountsPlugin

14 Master Tag Counts The individual tag count files are merged into a master tag count file. A minimum count is specified at the merge stage to exclude tags with low counts (likely sequencing errors). MergeMultipleTagCountsPlugin

15 Conversion of Tags to Fastq
Sequence aligners do not work with the tag count file format. In preparation for the alignment step, the Master Tag Count file is converted to fastq format. TagCountsToFastqPlugin

16 GBS Discovery Pipeline
Tag Counts SNP Caller Genotypes Tags by Taxa Sequence TOPM

17 Tag Alignment / TOPM The GBS pipeline uses an external aligner to do the initial alignment. The current version uses bowtie2 which produces the alignment in the SAM format. bowtie2 We convert the SAM file into our tags on physical map format (TOPM) SAMConverterPlugin

18 TOPM

19 So Far We Have Identified and counted GBS tags.
Converted tag counts file to fastq. Aligned the tags to a reference. Converted the alignment to TOPM.

20 GBS Discovery Pipeline
Tag Counts SNP Caller Genotypes Tags by Taxa Sequence TOPM

21 Tags by Taxa In this step we identify which tags are present in which taxa. Original Sequence Files Key File Master Tag Count File Recently migrated to HDF5 file format. Efficient storage Large data sets SeqToTBTHDF5Plugin

22 Tags By Taxa Additional Operations
If many TBTs have been created they are merged into 1 TBT. Taxa that were sequenced multiple times are merged. The TBT table is pivoted in preparation for SNP calling. ModifyTBTHDF5Plugin

23 GBS Discovery Pipeline
Tag Counts SNP Caller Genotypes Tags by Taxa Sequence TOPM

24 SNP Calling Files used in SNP Calling Some Key Settings TOPM TBT
Pedigree File (optional) Some Key Settings mnF MinimumF (inbreeding coefficient) mnMAF Minimum Minor Allele Frequency mnMAC Minimum Minor Allele Count mnLCov Minimum Locus Coverage TagsToSNPByAlignmentPlugin

25 HapMap rs# alleles chrom pos strand SgSBRIL067:633Y5AAXX:2:C9 SgSBRIL019:633Y5AAXX:2:C3 S1_2100 A/G N N N N N N N R N A N S1_2163 T/C N N N N N N T C T T N S1_13837 T/G N N N N N N N G N N T S1_14606 C/T N N C N N N T T T T C S1_2061 T/A T N N N N N N A N N N S1_68332 C/T N N N N N N N N N N N S1_68596 A/T A N N N N N N N N A N S1_69309 G/A N G N N N N N A N N N S1_79955 T/G N T G T T N T T N N N S1_79961 T/G N T T T T N T T N N N S1_80584 G N N N N N N N N N N G S1_80647 C/T N N N N N N N C N N C S1_81274 T/G N N N N N N T G N N N S1_ G/A N N N N N N N N N N N S1_ T/G N N N N N N K T N N N S1_ C/T N N N N N N T C N T S1_ T/C N N N N N N N C N N N S1_ G/A G G A N N G G G G N S1_ T/G N N T N N N T T N N T S1_ A/G N A G N N N G A N N N S1_ C/T N N N N C N N C N N N S1_ T/C N T N N N N

26 GBS Discovery pipeline
Fastq Tags by Taxa Tag Counts TOPM SNP Caller Genotypes

27 GBS Discovery pipeline
Fastq Tags by Taxa Tag Counts TOPM SNP Caller Genotypes Filtered Genotypes

28 Production Pipeline

29 Why another pipeline? The last maize build (30000 taxa) with the discovery pipeline took weeks. Most common alleles have been identified after the first few discovery builds. Use the information from the discovery pipeline to call SNPs in new runs quickly. Improve efficiency and automate.

30 GBS Bioinformatics Pipelines
Discovery Production Fastq Fastq Tags by Taxa Tag Counts TOPM SNP Caller Genotypes

31 TagsOnPhysicalMap (TOPM)
Discovery Production Fastq Fastq Tags by Taxa Tag Counts TOPM SNP Caller Genotypes

32 GBS Bioinformatics Pipelines
Discovery Production Fastq Fastq Tags by Taxa Tag Counts TOPM SNP Caller Genotypes Filtered Genotypes

33 GBS Bioinformatics Pipelines
Discovery Production Fastq Fastq Tags by Taxa Tag Counts TOPM TOPM SNP Caller Genotypes Filtered Genotypes

34 GBS Bioinformatics Pipelines
Discovery Production Fastq Fastq Tags by Taxa Tag Counts TOPM TOPM SNP Caller Genotypes Filtered Genotypes

35 GBS Bioinformatics Pipelines
Discovery Production Fastq Fastq Tags by Taxa Tag Counts TOPM TOPM SNP Caller Genotypes Filtered Genotypes Genotypes

36 Running the Production Pipeline
Required Files: Sequence file (fastq or qseq) Key file Production TOPM TASSEL 3 Standalone & RawReadsToHapMapPlugin Running the Pipeline: One lane processed at a time HapMap files by chromosome ~40 minutes

37 Testing Production Pipeline
Compared HapMap files produced by Discovery Pipeline and Production Pipeline Site Comparison: Discovery 48,139 Production 47,676 Difference due to maximum 8 alleles 99.98% correlation of genetic distance matrices

38 Next Steps In Pipeline Development
Hierarchical Data Format – supports very large data sets and complex data structures. Working to fuse TOPM, TBT, Keyfile, and Pedigree File into one HDF5 repository. Continued improvements to SNP caller. Ability to use tags not present in the reference.

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