TPES_purity

0th

Percentile

Tumor Purity Estimation using SNVs

TPES_purity function estimates tumor purity.

Usage
TPES_purity(ID, SEGfile, SNVsReadCountsFile, ploidy, RMB = 0.47,
maxAF = 0.55, minCov = 10, minAltReads = 5, minSNVs = 10)
Arguments
ID

Sample ID. Must be the same ID as in SEGfile, SNVsReadCountsFile and ploidy.

SEGfile

A standard SEG file (segmented data). It is a data frame object that lists loci and associated numeric values. The header must be compatible with the standard format defined by the Broad Institute. For more information please visit SEG file format.

A standard MAF (Mutation Annotation Format) file. It is a data frame object containing the read counts data of somatic single nucleotide variants (SNVs) loci. The header must contains at least informations about the chromosme that harbors the SNV ("chr" column), the position of the SNV (defined by the "start" and "end" columns), the sample ID ("sample" column) and finally the informations about the reference and alternative base counts ("ref.count" and "alt.count" columns, respectively). For more information please visit MAF file format.

ploidy

A data frame containing the ploidy status of a sample. It must contain at least the sample ID ("sample" column) and the ploidy status ("ploidy" column).

RMB

The Reference Mapping Bias value. The reference genome contains only one allele at any given locus, so reads that carry a non-reference allele are less likely to be mapped during alignment; this causes a shift from 0.5. It can be estimated as: $1 - medAF$, where medAF is the median value of the allelic fraction of the sample's germline heterozygous SNPs. Default is set to 0.47. For more informations see: PMID: 19808877.

maxAF

The filter on the allelic fraction (AF) distribution of SNVs. This is necessary to be sure to keep only heterozygous SNVs. Clonal and subclonal SNVs, which have an AF greater than maxAF, will be removed.

minCov

The minimum coverage for a SNV to be retained.

The minimum coverage for the alternative base of a SNV to be retained.

minSNVs

The minimum number of SNVs required to make a purity call.

Value

TPES returns a data.frame object with one row per sample and the following columns:

sample

The sample ID;

purity

The sample purity estimated by TPES;

purity.min

The sample minimum purity estimated by TPES;

purity.max

The sample maximum purity estimated by TPES;

n.segs

The number of copy number neutral segments used by TPES;

n.SNVs

The number of SNVs used by TPES;

RMB

The Reference Mapping Bias value used to estimate the tumor purity;

BandWidth

The smoothing bandwidth value of the density function chosen by TPES.

log

Reports if the run was successful; otherwise provides debugging information.

• TPES_purity
Examples
# NOT RUN {
## Compute tumor purity for samples "TCGA-A8-A0A7" and "TCGA-HT-8564"
## https://cancergenome.nih.gov/
## Please copy and paste the following lines:
library(TPES)
TPES_purity(ID = "TCGA-A8-A0A7", SEGfile = TCGA_A8_A0A7_seg,
SNVsReadCountsFile = TCGA_A8_A0A7_maf, ploidy = TCGA_A8_A0A7_ploidy,
RMB = 0.47, maxAF = 0.55, minCov = 10, minAltReads = 5, minSNVs = 10)

TPES_purity(ID = "TCGA-HT-8564", SEGfile = TCGA_HT_8564_seg,
SNVsReadCountsFile = TCGA_HT_8564_maf, ploidy = TCGA_HT_8564_ploidy,
RMB = 0.47, maxAF = 0.55, minCov = 10, minAltReads = 5, minSNVs = 10)

# }

Documentation reproduced from package TPES, version 1.0.0, License: MIT + file LICENSE

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