| estep {ebGenotyping} | R Documentation |
E step
Description
This function calculates the E step of ECM algorithm for the model described in 'An Empirical Bayes Method for Genotyping and SNP detection Using Multi-sample Next-generation Sequencing Data'.
Usage
estep(mu, delta, pm1, p0, dat, cvg)
Arguments
mu |
a vetor of the same length as number of positions: the position effect. |
delta |
a vetor of the same length as number of samples: the sample effect. |
pm1 |
a single value,which is larger than 0 and less than 1: the probability of RR. |
p0 |
a single value,which is larger than 0 and less than 1: the probability of RV. |
dat |
a n*m matrix: the ith row, jth column of the matrix represents the non-reference counts of ith sample at jth position. |
cvg |
a n*m matrix: the ith row, jth column of the matrix represents the depth of ith sample at jth position. |
Details
The value of mu and delta must satisfy that each element of outer(delta,mu,"+") must less than zero. This is the requirement of the model described in paper "Genotyping for Rare Variant Detection Using Next-generation Sequencing Data."
Value
zRR |
a n*m matrix: the posterior probabilities of genotype RR for n samples at m positions |
zRV |
a n*m matrix: the posterior probabilities of genotype RV for n samples at m positions |
zVV |
a n*m matrix: the posterior probabilities of genotype VV for n samples at m positions |
Note
The most important function in this package is "ecm". "estep" is a function called by "ecm" to realize one E step in the whole process of iteration in "ecm".
Author(s)
Na You <youn@mail.sysu.edu.cn> and Gongyi Huang<53hgy@163.com>
References
Na You and Gongyi Huang.(2016) An Empirical Bayes Method for Genotyping and SNP detection Using Multi-sample Next-generation Sequencing Data.