calculatePowerDetectSomatic: Power calculation for detecting somatic mutations

In lima1/PureCN: Copy number calling and SNV classification using targeted short read sequencing

Power calculation for detecting somatic mutations

Description

This function calculates the probability of correctly rejecting the null hypothesis that an alt allele is a sequencing error rather than a true (mono-)clonal mutation.

Usage

calculatePowerDetectSomatic(
  coverage,
  f = NULL,
  purity = NULL,
  ploidy = NULL,
  cell.fraction = 1,
  error = 0.001,
  fpr = 5e-07,
  verbose = TRUE
)

Arguments

coverage	Mean sequencing coverage.
f	Mean expected allelic fraction. If NULL, requires purity and ploidy and then calculates the expected fraction.
purity	Purity of sample. Only required when f is NULL.
ploidy	Ploidy of sample. Only required when f is NULL.
cell.fraction	Fraction of cells harboring mutation. Ignored if f is not NULL.
error	Estimated sequencing error rate.
fpr	Required false positive rate for mutation vs. sequencing error.
verbose	Verbose output.

Value

A list with elements

power	Power to detect somatic mutations.
k	Minimum number of supporting reads.
f	Expected allelic fraction.

Author(s)

Markus Riester

References

Carter et al. (2012), Absolute quantification of somatic DNA alterations in human cancer. Nature Biotechnology.

Examples

purity <- c(0.1, 0.15, 0.2, 0.25, 0.4, 0.6, 1)
coverage <- seq(5, 35, 1)
power <- lapply(purity, function(p) sapply(coverage, function(cv)
    calculatePowerDetectSomatic(coverage = cv, purity = p, ploidy = 2,
    verbose = FALSE)$power))

# Figure S7b in Carter et al.
plot(coverage, power[[1]], col = 1, xlab = "Sequence coverage",
    ylab = "Detection power", ylim = c(0, 1), type = "l")

for (i in 2:length(power)) lines(coverage, power[[i]], col = i)
abline(h = 0.8, lty = 2, col = "grey")
legend("bottomright", legend = paste("Purity", purity),
    fill = seq_along(purity))

# Figure S7c in Carter et al.
coverage <- seq(5, 350, 1)
power <- lapply(purity, function(p) sapply(coverage, function(cv)
    calculatePowerDetectSomatic(coverage = cv, purity = p, ploidy = 2,
        cell.fraction = 0.2, verbose = FALSE)$power))
plot(coverage, power[[1]], col = 1, xlab = "Sequence coverage",
    ylab = "Detection power", ylim = c(0, 1), type = "l")

for (i in 2:length(power)) lines(coverage, power[[i]], col = i)
abline(h = 0.8, lty = 2, col = "grey")
legend("bottomright", legend = paste("Purity", purity),
    fill = seq_along(purity))

lima1/PureCN documentation built on Nov. 22, 2024, 6:07 a.m.