Down-sampling uses subsets of reads from primary sequencing data of validated somatic mutations to measure the sensitivity with which a mutation caller identifies the known mutations. Subsets are generated by randomly excluding reads from the experimentally-derived data set until a desired depth of coverage is reached. Notably, down-sampling preserves the expected allelic fraction of the original mutation because reads are removed regardless whether or not they contain the mutant allele. The down-sampling approach is limited in four respects: (i) the number of validated events is typically small, resulting in larger error bars for the sensitivity estimate; (ii) because allele fractions are preserved, only previously validated allele fractions can be explored; (iii) the analysis excludes any mutations that were not originally detected and hence may overestimate the true sensitivity; and (iv) specificity cannot be measured.
