compute_beta_table {CLONETv2}

Function to compute beta table

Description

This function takes segmented data and per base pileup of tumor and matched normal of a sample as input and associates a beta value to each genomic segment.

Usage

compute_beta_table(seg_tb, pileup_tumor, pileup_normal,
  min_coverage = 20, min_required_snps = 10, min_af_het_snps = 0.2,
  max_af_het_snps = 0.8, n_digits = 3, n_cores = 1, plot_stats = F,
  debug = F)

Arguments

seg_tb

data.frame in SEG format. Rows report per segment log2 ratio numeric value. CLONETv2 inteprets first column as sample name, columns two to four as genomic coordinates (chromosome, start location, and end location), column five is not used, and column six is the log2 ratio returned by segmentation algorithm.

pileup_tumor, pileup_normal

data.frame reporting pileup of SNPs in tumor and normal samples respectively. First row contains column names and subsequent rows report the pileup of a specific genomic positions. Required information for each genomic position includes chromosome, position, allelic fraction, and coverage. Required column names are chr, pos, af, and cov

min_coverage

minimum number of reads for considering a pileup position valid (default=20)

min_required_snps

minimum number of snps to call beta for a segment (default=10)

min_af_het_snps

minimum allowed allelic fraction of a SNP genomic position (default=0.2)

max_af_het_snps

maximum allowed allelic fraction of a SNP genomic position (default=0.8)

n_digits

number of digits in the output table (default=3)

n_cores

number of available cores for computation (default=1)

plot_stats

plot summary statistics of the computed beta table (default=F)

debug

return extra columns for debugging (default=F)

Value

A data.frame that extends input seg_tb with columns beta, nsnp, cov, n_beta. Moreover, CLONETv2 renames colums of seg_tb as sample, chr, start, end, XYZ, log2, with XYZ being the original name of column five As for seg_tb, each raw of the output table represents a genomic segments. For each raw, the value of beta is the proportion of neutral reads in the segment, while nsnp and cov represents respectively the number of informative SNPs and the mean coverage of the given segment. The value n_beta is the proportion of neutral reads in the normal sample. The value of n_beta should be 1 as in normal samples parental chromosomes are equally represented. Values lower than 1 of n_beta could indicate the presence of germline CNVs or sequencing errors.

Author(s)

Davide Prandi, Alessandro Romanel

Examples

## Compue beta table with default parameters
bt_toy <- compute_beta_table(seg_tb_toy, pileup_tumor_toy, pileup_normal_toy)