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.

[Package ebGenotyping version 2.0.1 Index]