Difference between revisions of "Thunder"
| Line 30: | Line 30: | ||
== Important Filters == | == Important Filters == | ||
| + | |||
| + | We have found that the following filters are helpful. | ||
| + | |||
| + | === total depth filter === | ||
| + | For the 1000 Genomes Project (average depth per individual ~4X), we have found it useful to exclude sites with average total depth per individual < 0.5X or > 10X. | ||
Revision as of 15:51, 15 October 2010
This page documents how to perform variant calling from low-coverage sequencing data using glfmultiples and thunder. The pipeline was originally developed by Yun Li for the 1000 Genomes Low Coverage Pilot Project.
Input Data
To get started, you will need glf files in the standard format glf format. Sample files are available at sample glf files.
If you do not have glf files, you can generate them from bam files (bam format also specified in glf format bam format) using the following command line:
samtools pileup -g -T 1 -f ref.fa my.bam > my.glf
Note: you will need the reference fasta file ref.fa to create glf file from bam file.
How to Run
This variant calling pipeline has two steps. (step 1) promotion of a set of potential polymorphisms; and (step 2) genotype/haplotype calling using LD information.
(step 1) Site promotion using software glfMultiples GPT_Freq.
GPT_Freq -b my.out -p 0.9 --minDepth 10 --maxDepth 1000 *.glf
(step 2) Genotype/haplotype calling using thunder thunder_glf_freq.
thunder_glf_freq --shotgun my.out.$chr -r 100 --states 200 --dosage --phase --interim 25 -o my.final.out
Notes:
(1) The program thunder used in step 2 is an extension of MaCH, the genotype imputation software we have previously developed. For details regarding the shared options, please check out MaCH website and MaCH wiki.
(2) Check out example files and command lines under examples/thunder/ in the thunder package thunder_glf_freq.
Important Filters
We have found that the following filters are helpful.
total depth filter
For the 1000 Genomes Project (average depth per individual ~4X), we have found it useful to exclude sites with average total depth per individual < 0.5X or > 10X.
