| mstep {ebGenotyping} | R Documentation |
CM steps
Description
This function calculates the CM steps 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
mstep(mu0, delta0, zm1, z0, zp1, dat, cvg, eps = 1e-06)
Arguments
mu0 |
a vetor of the same length as number of positions: the initial value of position effect mu. |
delta0 |
a vetor of the same length as number of samples: the initial value of sample effect delta. |
zm1 |
the output of estep: the posterior probabilities of genotype RR for n samples at m positions |
z0 |
the output of estep: the posterior probabilities of genotype RV for n samples at m positions |
zp1 |
the output of estep: the posterior probabilities of genotype VV for n samples at m positions |
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. |
eps |
a single value: a threshold to control the convergence criterion. The default is 1e-06. |
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 'An Empirical Bayes Method for Genotyping and SNP detection Using Multi-sample Next-generation Sequencing Data'.
Value
mu |
the optimal value of mu in current CM steps |
delta |
the optimal value of delta in current CM steps |
pRR |
the optimal value of the probability of RR in current CM steps |
pRV |
the optimal value of the probability of RV in current CM steps |
Note
The most important function in this package is "ecm". "mstep" is a function called by "ecm" to realize one M step(several CM steps) 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.