grad_parent: Gradient of 'obj_parent' (when 'outlier = FALSE') with...
In dcgerard/updogAlpha: Using Parental Data for Offspring Genotyping

Description Usage Arguments Value Author(s)

Gradient of obj_parent (when outlier = FALSE) with respect to bias_val, seq_error, and od_param. Basically, this just calculates derivatives of the log beta-binomial density.

1 2	grad_parent(pcounts, psize, ploidy, pgeno, bias_val = 1, seq_error = 0, od_param = 0, weight = 1)

`pcounts`	The number of counts of the reference allele we observe in a parent.
`psize`	The total number of reads we observe in a parent.
`ploidy`	An integer. The ploidy of the species. This is assumed to be the same for each individual.
`pgeno`	The genotype of the parent.
`bias_val`	The bias parameter. A value of 1 means there is no bias toward one allele or the other. A value less than one indicates a bias toward the reference allele. A value greater than one indicates a bias toward the non-reference allele.
`seq_error`	The sequencing error rate.
`od_param`	The overdispersion parameter in the beta-binomial model for the OK counts. When this is zero, this resorts to the binomial model for counts.
`weight`	A double that multiplies to the log-likelihood (objective). Should only be used when `outlier = FALSE` during the M step of the EM algorithm.