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gmt music

NAME

       gmt music - Mutational Significance in Cancer (Cancer Mutation Analysis)

VERSION

       This document describes gmt music version 0.04 (2018-07-05 at 09:17:13)

SYNOPSIS

       gmt music ...

DESCRIPTION

The MuSiC suite is a set of tools aimed at discovering the significance of somatic mutations found within
a given cohort of cancer samples, and with respect to a variety of external data sources. The standard
inputs required are:

1. mapped reads in BAM format
2. predicted or validated SNVs or indels in mutation annotation format (MAF)
3. a list of regions of interest (typically the boundaries of coding exons)
4. any relevant numeric or categorical clinical data.

The formats for inputs 3. and 4. are:

3. Regions of Interest File:
• Do not use headers

• 4 columns, which are [chromosome start-position(1-based) stop-position(1-based) gene_name]

4. Clinical Data Files:
• Headers are required

• At least 1 sample_id column and 1 attribute column, with the format being [sample_id
clinical_data_attribute clinical_data_attribute ...]

• The sample_id must match the sample_id listed in the MAF under "Tumor_Sample_Barcode" for
relating the mutations of this sample.

• The header for each clinical_data_attribute will appear in the output file to denote
relationships with the mutation data from the MAF.

Descriptions for the usage of each tool (each sub-command) can be found separately.

The play command runs all of the sub-commands serially on a selected input set.

SUB-COMMANDS

   GENERAL
       bmr
           Calculate gene coverages and background mutation rates.

       clinical-correlation
           Correlate phenotypic traits against mutated genes, or against individual variants

       cosmic-omim
           Compare the amino acid changes of supplied mutations to COSMIC and OMIM databases.

       galaxy
           Run the full suite of MuSiC tools sequentially.

       mutation-relation
           Identify relationships of mutation concurrency or mutual exclusivity in genes across cases.

       path-scan
           Find significantly mutated pathways in a cohort given a list of somatic mutations.

       pfam
           Add Pfam annotation to a MAF file

       play
           Run the full suite of MuSiC tools sequentially.

       plot
           Generate relevant plots and visualizations for MuSiC.

       proximity
           Perform a proximity analysis on a list of mutations.

       smg
           Identify significantly mutated genes.

       survival
           Create survival plots and P-values for clinical and mutational phenotypes.

LICENSE

       Copyright (C) 2007-2011 Washington University in St. Louis.

       It is released under the Lesser GNU Public License (LGPL) version 3.  See the associated LICENSE file  in
       this distribution.

AUTHORS

       This  software  is  developed by the analysis and engineering teams at The Genome Institute at Washington
       University School of Medicine in St.  Louis,  with  funding  from  the  National  Human  Genome  Research
       Institute.  Richard K. Wilson, P.I.

       The primary authors of the MuSiC suite are:

        Nathan D. Dees, Ph.D.
        Cyriac Kandoth, Ph.D.
        Dan Koboldt, M.S.
        William Schierding, M.S.
        Michael Wendl, Ph.D.
        Qunyuan Zhang, Ph.D.
        Thomas B. Mooney, M.S.

CREDITS

       The MuSiC suite uses tabix, by Heng Li.  See http://samtools.sourceforge.net/tabix.shtml.

       MuSiC  depends  on  copies  of  data  from  the following databases, packaged in a form useable for quick
       analysis:

        * KEGG - http://www.genome.jp/kegg/
        * COSMIC - http://www.sanger.ac.uk/genetics/CGP/cosmic/
        * OMIM - http://www.ncbi.nlm.nih.gov/omim
        * Pfam - http://pfam.sanger.ac.uk/
        * SMART - http://smart.embl-heidelberg.de/
        * SUPERFAMILY - http://supfam.cs.bris.ac.uk/SUPERFAMILY/
        * PatternScan - http://www.expasy.ch/prosite/

BUGS

       For defects with any software in the genome namespace, contact
        genome-dev ~at~ genome.wustl.edu.