diffVariantError: differentiate a variant from sequencing error
In hiPOD: hierarchical Pooled Optimal Design

Description Usage Arguments Details Value Author(s) Examples

This function finds a practical threshold to differentiate a variant call from sequencing error.

1	diffVariantError(Xmean, N.p, error, N.test = 1)

`Xmean`	The average coverage on the pool
`N.p`	The pool size: number of individuals per pool
`error`	Sequencing error rate
`N.test`	Number of tests, usually the same as number of pools P

It is a helper function to calculate the probability of detection.

diffVariantError() returns a vector c(v, p0, p1), where v is the threshold for a variant call, p0 is the false discovery rate and p1 is the lower bound of true discovery rate.

Wei E. Liang

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function(Xmean, N.p, error, N.test=1)
{
	theta <- (1-error)/(2*N.p) + error*(1-1/(2*N.p))

	for(v in 1:Xmean)
	{
		p1 <- pbinom(v-1, Xmean, theta, lower.tail=FALSE)
		p0 <- pbinom(v-1, Xmean, error, lower.tail=FALSE)
		
		if(p1/p0 > 5 & p0<0.05/N.test) break;
	}
	
	c(v, p0, p1)
  }