The required depth of coverage can be estimated based on the required lower limit of detection, the quality of the reads, and tolerance for false-positive or false-negative results.
For example, for a given proportion of mutant alleles, the probability of detecting a minimum number of alleles can be determined using the binomial distribution equation:
\[ P(x)=\frac{n!}{x!(n-x)!} p^x(1-p)^{n-x} \] Where \(P(x)\) is the probability of \(x\) variant reads, \(x\) is the number of variant reads, \(n\) is the number of total reads, and \(p\) is the probability of detecting a variant allele (ie, the proportion of mutant alleles in the sample).
By calculating the binomial probability for a given number of trials and probability of successes, one can define the binomial distribution.
For example, for a given mutant allele frequency of 5% and 250 reads, the probability of detecting four or fewer mutations would be \[0.457\%\] .
sum(dbinom(0:4,250,0.05))
## [1] 0.004570736
Therefore, the probability of detecting of five or more mutations is 1 minus 0.457% (or 99.543%).
1-sum(dbinom(0:4,250,0.05))
## [1] 0.9954293
Thus, if the threshold for a variant call were set at five or more reads, the probability of a false negative would be <0.5% provided a minimum of 250 reads were obtained. For clinical NGS panels, a minimal depth of coverage of 250 reads per tested amplicon or target is strongly recommended.