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Q: Where can I find the mutation rates calculated during Firehose analyses?

A: Mutation rates are calculated by MutSig, and can be found in the patient_counts_and_rates.txt file bundled within the MutSig result archives. You can retrieve these archives with firehose_get or through the user interface (e.g. here is a link for MutSig2CV analysis results for adrenocortical carcinoma, or ACC). In addition, we plan to add mutation rates to the FireBrowse api in the near future.

Q: What are the differences between MutSig 1.5, 2.0, CV, and

A: MutSig relies on several sources of evidence in the data to estimate the amount of positive selection a gene underwent during tumorigenesis. The three main sources are:

  1. Abundance of mutations relative to the background mutation rate (BMR)
  2. Clustering of mutations in hotspots within the gene
  3. Conservation of the mutated positions (i.e. did the mutation happen at a position that is conserved across vertebrates?)

The first line of evidence, Abundance, goes into the core significance calculation performed in all versions of MutSig. In MutSig1.0, this is simply called "p". MutSig1.0 assumes a constant BMR across all genes in the genome and all patients in the patient cohort. In MutSig1.5, this is also called "p", but MutSig1.5 uses information from synonymous mutations to roughly estimate gene-specific BMRs. Later versions of MutSig (MutSigS2N and MutSigCV) have increasingly sophisticated procedures for treating the heterogeneity in per-gene, per-patient, and per-context BMRs, but they are all answering essentially the same question about Abundance of mutations above the background level.

The other lines of evidence, Conservation and Clustering, are examined by a separate part of MutSig that performs many permutations, comparing the distributions of mutations observed to the null distribution from these permutations. The output of this permutation procedure is a set of additional p-values: p_clust is the significance of the amount of clustering in hotspots within the gene. p_cons is the significance of the enrichment of mutations in evolutionarily conserved positions of the gene. Finally, p_joint is the joint significance of these two signals (Conservation and Clustering), calculated according to their joint distribution. The reason for calculating p_joint is to ensure there is no double-counting of the significance due, for example, to clustering in a conserved hotspot.

Combining MutSig2CV combines all three lines of evidence: In order to take a full accounting of the signals of positive selection in a given gene, we combine all three lines of evidence. This is done by using the Fisher method of combining p-values. The two p-values combined are the "p" (or "p_classic") from the analysis of mutation Abundance, and the p_joint from the analysis of Conservation and Clustering in MutSig2.0. More information on MutSig is available on its entry in the CGA software page, the 2013 and 2014 MutSig publications and dozens of TCGA-related papers.


. More information on MutSig is available on its entry in the CGA software page, the 2013 and 2014 MutSig publications, dozens of TCGA-related papers, and in their respective reports.

Q: What do the different fields for significantly mutated genes mean?

A: Many of these fields depend on what version of MutSig was used. The following table covers the majority of them:

genegenegenegeneHUGO Symbol
descriptiondescription longnameFull description/name of the gene
NN  number of sequenced bases in this gene across the individual set
nn  number of (nonsilent) mutations in this gene across the individual set
  nnonnnonnumber of nonsense mutations
npatnpatnpatnpatnumber of patients (individuals) with at least one nonsilent mutation
nsitensitensitensitenumber of unique sites having a nonsilent mutation
nsilnsilnsilnsilnumber of silent mutations in this gene across the individual set
n1n1  number of nonsilent mutations of type "*CpG->T"
n2n2  number of nonsilent mutations of type "*Cp(A/C/T)->T*"
n3n3  number of nonsilent mutations of type "A->G"
n4n4  number of nonsilent mutations of type "transver"
n5n5  number of nonsilent mutations of type "indel+null"
n6n6  number of nonsilent mutations of type "double_null"
p_ns_sp_ns_s  p-value for the observed nonsilent/silent ratio being elevated in this gene
ppppp-value (overall)
qqqqq-value, False Discovery Rate (Benjamini-Hochberg procedure)
 p_classic  p-value for the observed amount of nonsilent mutations being elevated in this gene
 p_clust pCLp-value for clusteringClustering. Probability that recurrently mutated loci in this gene have more mutations than expected by chance. While pCV assesses the gene's overall mutation burden, pCL assesses the burden of specific sites within the gene. This allows MutSig to differentiate between genes with uniformly distributed mutations and genes with localized hotspots.
 p_cons pFNp-value for conservationConservation. Probability that mutations within this gene occur disproportionately at evolutionarily conserved sites. Sites highly conserved across vertebrates are assumed to have greater functional impact than weakly conserved sites.
 p_joint  p-value for joint model of clustering and conservation
   pCVp-value from covariatesAbundance. Probability that the gene's overall nonsilent mutation rate exceeds its inferred background mutation rate (BMR), which is computed based on the gene's own silent mutation rate plus silent mutation rates of genes with similar covariates. BMR calculations are normalized with respect to patient-specific and sequence context-specific mutation rates.
   codelenthe gene's coding length
   nncdnumber of noncoding mutations
   nmisnumber of missense mutations
   nstpnumber of readthrough mutations
   nsplnumber of splice site mutations
   nindnumber of indels