obj_parent: Parent contribution to objective function.
In dcgerard/updogAlpha: Using Parental Data for Offspring Genotyping

For each parental read counts you have, add this to {obj_offspring} to get the objective function.

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obj_parent(pcounts, psize, ploidy, pgeno, bias_val = 1, seq_error = 0,
  od_param = 0, outlier = FALSE, out_prop = 0.01, out_mean = 0.5,
  out_disp = 1/3, 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.
`outlier`	A logical. Should we include an outlier model (`TRUE`) or not (`FALSE`)? Defaults to `FALSE`.
`out_prop`	The proportion of points that are outliers. Defaults (quite arbitrarily) to `0.01`.
`out_mean`	The mean of beta-binomial for the outlier distribution. Defaults to `0.5`.
`out_disp`	The overdispersion parameter of the outlier distribution. Defaults to `1/3`, which corresponds to a uniform distribution for the underlying beta when `out_mean = 0.5`.
`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.