genome :: music
sub commands
proximity | Perform a proximity analysis on a list of mutations. |
cosmic-omim | Compare the amino acid changes of supplied mutations to COSMIC and OMIM databases. |
play | Run the full suite of MuSiC tools sequentially. |
clinical-correlation | Correlate phenotypic traits against mutated genes, or against individual variants |
pfam | Add Pfam annotation to a MAF file |
mutation-relation | Identify relationships of mutation concurrency or mutual exclusivity in genes across cases. |
smg | Identify significantly mutated genes. |
plot | Generate relevant plots and visualizations for MuSiC. |
survival | Create survival plots and P-values for clinical and mutational phenotypes. |
path-scan | Find signifcantly mutated pathways in a cohort given a list of somatic mutations. |
bmr | Calculate gene coverages and background mutation rates. |
genome music
NAME
genome music - Mutational Significance in Cancer (Cancer Mutation Analysis)
VERSION
This document describes genome music version 0.0401 (2013-12-30 at 16:01:08)
SYNOPSIS
genome 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.
LICENSE
Copyright (C) 2007-2013 Washington University in St. Louis.
MuSiC 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.
Development of MuSiC is funded by the National Human Genome Research Institute, grants #U54HG003079 (PI Richard K. Wilson) and #U01HG006517 (PIs Li Ding and David J. Dooling).
If you find MuSiC to be useful, please consider citing the reference that describes this work:
Nathan D. Dees, Qunyuan Zhang, Cyriac Kandoth, Michael C. Wendl, William Schierding, Daniel C. Koboldt, Thomas B. Mooney, Matthew B. Callaway, David Dooling, Elaine R. Mardis, Richard K. Wilson, and Li Ding. 2012. MuSiC: Identifying mutational significance in cancer genomes. Genome Research 22:1589-1598.
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.
SEE ALSO
genome(1)