create.mutation.matrix: Formatting matrix of mutations
In Clonality: Clonality testing

Description Usage Arguments Details Value Author(s) References Examples

This functions reformats matrix of mutations for subsequent analysis

1	create.mutation.matrix(maf,rem=FALSE)

maf

maf is a mutations file in generic MAF (mutation annotation format) style: one row per mutation per sample. See this webpage for detailed description of the format: https://docs.gdc.cancer.gov/Data/File_Formats/MAF_Format/ . Object 'maf' should have the following columns: PatientID, Tumor_Sample_Barcode (sample ID), Chromosome, Start_Position, Reference_Allele, Tumor_Seq_Allele2 (reference allele. For compatibility with mutational frequencies that can be obtained using function "get.mutation.frequencies" chromosome should be a number 1-22 or X or Y; Start_Position is genomic location in GRCh37 build; Reference_Allele is a reference allele and Tumor_Seq_Allele2 is Alternative allele. Mutation IDs are created, e.g. '10 100003849 G A' is the mutation at chromosome 10, genomic location 100003849, where reference allele G is substituted with A, or '10 100011448 - CCGCTGCAAT' is the insertion of 'CCGCTGCAAT' at chromosome 10, location 100011448. The ref and alt alleles follow standard TCGA maf file notations.

rem

if TRUE, the mutationan matrix for random effect function will be prepared.

if rem=FALSE (default), binary mutational matrix will be created, where each row is a mutation, each column is a sample, and values are binary taking values 0 if there is no mutation, 1 if there is a mutation in this sample. If rem=TRUE matrix with each possible pair of samples from the same patient will be created. Each row represents mutation, and each column - pair of samples, where value 0 denotes that mutation is not observed, 1 if shared mutation is observed in both tumors, and 2 if it is a private mutation observed in only one tumor.

Data frame with matrix of mutations

Irina Ostrovnaya ostrovni@mskcc.org

Ostrovnaya, Irina, Venkatraman E. Seshan, and Colin B. Begg. 2015. USING SOMATIC MUTATION DATA TO TEST TUMORS FOR CLONAL RELATEDNESS. The Annals of Applied Statistics 9 (3): 1533-48.

data(lcis)
#we want to analyze pair TK53IDC2.TK53LCIS2 that has only 1 shared mutation

mut.matrix<-create.mutation.matrix(lcis )
table(mut.matrix$TK53IDC2,mut.matrix$TK53LCIS2)

freq<-get.mutation.frequencies(rownames(mut.matrix),"BRCA") 
SNVtest(mut.matrix$TK53IDC2,mut.matrix$TK53LCIS2,freq)