. These measure the significance of mutation burden,
						  clustering, and functional impact, respectively [&hellip;].
						  MutSigCV determines the P value for observing the
						  given quantity of non-silent mutations in the gene,
						  given the background model determined by silent (and
						  noncoding) mutations in the same gene and the
						  neighbouring genes of covariate space that form its
						  'bagel'. [&hellip;] MutSigCL and MutSigFN measure the
						  significance of the positional clustering of the
						  mutations observed, as well as the significance of the
						  tendency for mutations to occur at positions that are
						  highly evolutionarily conserved (using conservation as
						  a proxy for probably functional impact). MutSigCL and
						  MutSigFN are permutation-based methods and their P
						  values are calculated as follows: The observed
						  nonsilent coding mutations in the gene are permuted T
						  times (to simulate the null hypothesis, T = 108 for
						  the most significant genes), randomly reassigning
						  their positions, but preserving their mutational
						  'category', as determined by local sequence context.
						  We [use] the following context categories: transitions
						  at CpG dinucleotides, transitions at other C-G base
						  pairs, transversions at C-G base pairs, mutations at
						  A-T base pairs, and indels. Indels are unconstrained
						  in terms of where they can move to in the
						  permutations. For each of the random permutations, two
						  scores are calculated: SCL and SFN, measuring the
						  amount of clustering and function impact (measured by
						  conservation) respectively. SCL is defined to be the
						  fraction of mutations occurring in hotspots. A hotspot
						  is defined as a 3-base-pair region of the gene
						  containing many mutations: at least 2, and at least 2%
						  of the total mutations. SFN is defined to be the mean
						  of the base-pair-level conservation values for the
						  position of each non-silent mutation [&hellip;]. To determine
						  a PCL, the P value for the observed degree of
						  positional clustering, the observed value of SCL
						  (computed for the mutations actually observed), [is]
						  compared to the distribution of SCL obtained from the
						  random permutations, and the P value [is] defined to
						  be the fraction of random permutations in which SCL
						  [is] at least as large as the observed SCL. The P
						  value for the conservation of the mutated positions,
						  PFN, [is] computed analogously."