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ABSTRACT.md
README.md
__init__.py
combine_models.py
somatic_probability.py

README.md

Links!!!!

Datasets: http://52.89.192.184/hackseq/HCC1954_Exome_Data_for_HackSeq/

IGV: http://software.broadinstitute.org/software/igv/download_snapshot

IPython Notebook: http://ec2-52-89-192-184.us-west-2.compute.amazonaws.com/

BAM documentation: http://support.10xgenomics.com/genome-exome/software/pipelines/latest/output/bam

VCF documentation: http://support.10xgenomics.com/genome-exome/software/pipelines/latest/output/vcf

Getting the longranger 'environment'. On EC2 instance: source /hackseq/longranger-2.1.1/sourceme.bash

Pipeline Planning

run_freebayes(ref, bam, bed, out_vcf) - Pat

Runs freebayes to shortlist positions specified by a bed file. Processes the resulting VCF file into a simpler format with chrom, pos, ref, alt information.

count_position(pos, bam, ref) - Aman, Peng

Taking one position and counts the haplotype 1 and haplotype 2 read counts.

model_positions(position_counts)

Runs the statistical model on each position's read counts For each position, determines the max likelihood model.

call_all(position_list, bam, ref) - Aman

Wrapper around count_position() which loops it on all the the shortlisted positions.

write_output

Outputs into tabular format for downstream statistical analyses and sanity checks.

Output Format:

Tabular output with the following columns:

chrom, pos, h1_ref, h1_alt, h2_ref, h2_alt, un_ref, un_alt

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