Description Usage Arguments Value References Examples
bcgr.combine
function first calculates both somatic background mutation probabilities (using bcgr.lawrence and bcgr functions) and then it takes the average value for each gene
1 2 3 |
sample.mutations |
data frame in MAF like format.
Columns names/header in
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genes |
vector of genes which were sequenced.
Vector of unique values of Hugo_Symbol names (with possibility of more additional genes which did not have any SNV in the cohort).
Default is NULL value and then the list of the unique genes is taken from |
lengthGenes |
numeric vector of the lengths (suquenced) for all |
Variant_Classification |
(optional) integer/numeric value indicating which column in |
Hugo_Symbol |
(optional) integer/numeric value indicating which column in |
Tumor_Sample_Barcode |
(optional) integer/numeric value indicating which column in |
CCF |
(optional) integer/numeric value indicating which column in |
a numeric vector of the probabilites that a gene has a nonsilent mutation (not caused by cancer).
http://www.ncbi.nlm.nih.gov/pubmed/23770567.
1 2 3 4 5 | # First we need to calculate CCF
sample.genes.mutect <- CCF(sample.genes.mutect)
# Calculate somatic nonsilent background mutation probability
background <- bcgr.combine(sample.genes.mutect, length.genes$Hugo_Symbol, length.genes$Coverd_len)
head(background)
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