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PROGRAM:

NAME


genome music path-scan - Find signifcantly mutated pathways in a cohort given a list of
somatic mutations.

VERSION


This document describes genome music path-scan version 0.04 (2016-01-01 at 23:10:18)

SYNOPSIS


genome music path-scan --gene-covg-dir=? --bam-list=? --pathway-file=? --maf-file=?
--output-file=? [--bmr=?] [--genes-to-ignore=?] [--min-mut-genes-per-path=?]
[--skip-non-coding] [--skip-silent]

... music path-scan \
--bam-list input_dir/bam_file_list \
--gene-covg-dir output_dir/gene_covgs/ \
--maf-file input_dir/myMAF.tsv \
--output-file output_dir/sm_pathways \
--pathway-file input_dir/pathway_dbs/KEGG.txt \
--bmr 8.7E-07

REQUIRED ARGUMENTS


gene-covg-dir Text
Directory containing per-gene coverage files (Created using music bmr calc-covg)

bam-list Text
Tab delimited list of BAM files [sample_name, normal_bam, tumor_bam] (See Description)

pathway-file Text
Tab-delimited file of pathway information (See Description)

maf-file Text
List of mutations using TCGA MAF specifications v2.3

output-file Text
Output file that will list the significant pathways and their p-values

OPTIONAL ARGUMENTS


bmr Number
Background mutation rate in the targeted regions

Default value '1e-06' if not specified

genes-to-ignore Text
Comma-delimited list of genes whose mutations should be ignored

min-mut-genes-per-path Number
Pathways with fewer mutated genes than this, will be ignored

Default value '1' if not specified

skip-non-coding Boolean
Skip non-coding mutations from the provided MAF file

Default value 'true' if not specified

noskip-non-coding Boolean
Make skip-non-coding 'false'

skip-silent Boolean
Skip silent mutations from the provided MAF file

Default value 'true' if not specified

noskip-silent Boolean
Make skip-silent 'false'

DESCRIPTION


Only the following four columns in the MAF are used. All other columns may be left blank.

Col 1: Hugo_Symbol (Need not be HUGO, but must match gene names used in the pathway file)
Col 2: Entrez_Gene_Id (Matching Entrez ID trump gene name matches between pathway file and MAF)
Col 9: Variant_Classification
Col 16: Tumor_Sample_Barcode (Must match the name in sample-list, or contain it as a substring)

The Entrez_Gene_Id can also be left blank (or set to 0), but it is highly recommended, in
case genes are named differently in the pathway file and the MAF file.

ARGUMENTS


--pathway-file
This is a tab-delimited file prepared from a pathway database (such as KEGG), with the
columns: [path_id, path_name, class, gene_line, diseases, drugs, description] The
latter three columns are optional (but are available on KEGG). The gene_line contains
the "entrez_id:gene_name" of all genes involved in this pathway, each separated by a
"|" symbol.
For example, a line in the pathway-file would look like:

hsa00061 Fatty acid biosynthesis Lipid Metabolism 31:ACACA|32:ACACB|27349:MCAT|2194:FASN|54995:OXSM|55301:OLAH

Ensure that the gene names and entrez IDs used match those used in the MAF
file. Entrez IDs are not mandatory (use a 0 if Entrez ID unknown). But if a
gene name in the MAF does not match any gene name in this file, the entrez IDs
are used to find a match (unless it's a 0).

--gene-covg-dir
This is usually the gene_covgs subdirectory created when you run "music bmr calc-
covg". It should contain files for each sample that report per-gene covered base
counts.
--bam-list
Provide a file containing sample names and normal/tumor BAM locations for each. Use
the tab- delimited format [sample_name normal_bam tumor_bam] per line. This tool only
needs sample_name, so all other columns can be skipped. The sample_name must be the
same as the tumor sample names used in the MAF file (16th column, with the header
Tumor_Sample_Barcode).
--bmr
The overall background mutation rate. This can be calculated using "music bmr calc-
bmr".
--genes-to-ignore
A comma-delimited list of genes to ignore from the MAF file. This is useful when there
are recurrently mutated genes like TP53 which might mask the significance of other
genes.

AUTHORS


Michael Wendl, Ph.D.

CREDITS


This module uses reformatted copies of data from the Kyoto Encyclopedia of Genes and
Genomes (KEGG) database:

* KEGG - http://www.genome.jp/kegg/

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