Overview and Implementation of the GBS Pipeline. Qi Sun Computational Biology Service Unit Cornell University

Transcription

1 Overview and Implementation of the GBS Pipeline Qi Sun Computational Biology Service Unit Cornell University

2 Overview of the Data Analysis Strategy

3 Genotyping by Sequencing (GBS) ApeKI site (GCWGC) ( ) 64 base sequence tag B73 < 450 bp Reduced genome representation; Reads can be aligned without reference genome;

4 Identification of markers with/without the reference genome B73 SNP and small INDELs Loss of cut site Mo17

5 Identification of Presence/Absence Variations (PAV) B73 Mo17

6 Reads > Tags > Call SNPs from Tags CAGCAAAAAAAAAAAAGAGGGATGGGGCGGCTTGCGTGCATGGGACACAAGCATGTAGACGGGC

7 Reads > Tags > Call SNPs from Tags Tag 1 Tag 2 Tag 3 CAGCAAAAAAAAAAAAGAGGGATGGGGCGGCTTGCGTGCATGGGACACAAGCATGTAGACGGGC.

8 Reads > Tags > Call SNPs from Tags Tag 1 Tag 2 Tassel Tag 2 Tag catalog is created from pooled Tag all 3 individuals. Tag 3. Stacks Tag catalog is created from each individual separately. CAGCAAAAAAAAAAAAGAGGGATGGGGCGGCTTGCGTGCATGGGACACAAGCATGTAGACGGGC

9 Reads > Tags > Call SNPs from Tags Tag 1 Maize NAM population (5000 lines) Tag billion reads 6 million tags Tag 3 CAGCAAAAAAAAAAAAGAGGGATGGGGCGGCTTGCGTGCATGGGACACAAGCATGTAGACGGGC.

10 Reads > Tags > Call SNPs from Tags Two ways of alignments: a. Anchored to reference genome (regular pipeline) b. Pair-wise alignment between tags (UNEAK)

11 Reads > Tags > Call SNPs from Tags ApeK I site tag1 tag2 tag3 CAGCAAAAAAAAAAAAGAGGGATGGGGCGGCTTGCGTGCATGGGACACAAGCGTATAGACGGGC Many tags with low read depth have sequencing errors.

12 Summary of the GBS pipeline Reads from a population Unique tag list from pooled reads Call SNPs from aligned tags

13 Summary of the GBS pipeline Reads from a population Unique tag list from pooled reads Call SNPs from aligned tags Match reads from each individual to the tags (tags to taxa matrix) Genotypes

14 Basic Filtering Strategy

15 Depth of Coverage Whole Genome Shotgun GBS Sites Depths Tags Depths #Depth

16 The GBS pipeline filtered out tags with very low read depth across the population WGS Reads from highly repetitive regions; GBS Reads with sequencing errors; Extremely rare alleles; Sites Tags Depths Depths

17 The GBS pipeline filtered out tags with very low read depth across the population WGS Reads from highly repetitive regions; GBS Reads with sequencing errors; Extremely rare alleles; Sites Depths Tags Generally we do not remove tags with very high depth. As they could come from a mix of (1) good loci with efficient PCR amplification; (2) bad loci from repetitive regions Depths

18 Uneven coverage enrich sequencing depth in some sites, but cause missing data in others Strategies 1. Filter out sites with too much missing data; 2. Filter out genotypes with low depth to minimize heterozygous genotyping errors. 3. Imputation based on haplotypes;

19 Filter genotyping errors Most of the genotyping errors are caused by reads from paralogous regions Individual A Reference genome Individual B Paralogous regions

20 Pipeline Implementation

21 Three ways to access the software 1. Computers with GBS software pre-installed Cornell BioHPC Lab iplant Discovery Environment 2. Using pre-compiled Java code from Get the source code from sourceforge.net (Project name: TASSEL)

22 GBS Pipeline on Cornell BioHPC Lab (for both Cornell and external users only) Step 1: Reserve a machine

23 GBS Pipeline on Cornell BioHPC Lab Step 2: Upload files Fetch (mac), FileZilla (win) or WinSCP (win)

24 GBS Pipeline on Cornell BioHPC Lab Step 3: Type the command to run pipeline Mac: terminal window; PC: Putty tassel/run_pipeline.pl -fork1 -QseqToTagCountPlugin -i. -k rice.key -e apeki -endplugin -runfork1

25 Using iplant Two ways to upload files to iplant data store 1. Web interface 2. Command line tool: icommand

26 GBS on iplant Discovery Environment (Beta version now)

27 Set up the pre-compiled pipeline on your own computer A computer with at least 8GB or more RAM (Linux or Mac) Download TASSEL Standalone from maizegenetics.net Set up Java (64bit) BWA (for alignment to reference genome) Document for installation: Download the zip file: TASSEL_x.x _Standalone

28 Set up TASSEL source code in Netbeans (make user use 64-bit Java and Netbeans)

29 The intermediate files are compressed binary files BinaryToTextPlugin can be used to convert to text file Tag Counts (TC): *.cnt.txt *.cnt Tag by taxa (TBT): *.tbt.txt *.tbt.bin Tags on physical map (TOPM): *.topm.txt *.topm.bin Hapmap *.hmp.txt GDPDM blobs * 64 bp tags were represented as 2 long integers (8 bytes for long in Java).