bb_simple_post: Simple posterior inference for beta-binomial when ncounts and...
In dcgerard/updogAlpha: Using Parental Data for Offspring Genotyping

Simple posterior inference for beta-binomial when ncounts and ssize are only length 1.

1 2	bb_simple_post(ncounts, ssize, ploidy, p1geno, p2geno, seq_error = 0, bias_val = 1, od_param = 0)

`ncounts`	A vector of non-negative integers. The ith element is the number of counts of the ith sample.
`ssize`	A vector of positive integers. The ith element is the total number of counts of the ith sample.
`ploidy`	The ploidy of the species.
`p1geno`	The first parental genotype.
`p2geno`	The second parental genotype.
`seq_error`	A non-negative numeric. This is the known sequencing error rate. This is a rough high-ball error rate given by Li et. al. (2011).
`bias_val`	The bias parameter. A value of 1 means no bias.
`od_param`	The over-dispersion parameter. A value of 0 means no overdispersion. A value of 1 means total overdispersion.