Description Usage Arguments Details Value Note Author(s) References

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'.

1 | ```
estep(mu, delta, pm1, p0, dat, cvg)
``` |

`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. |

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."

`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 |

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".

Na You <youn@mail.sysu.edu.cn> and Gongyi Huang<53hgy@163.com>

Na You and Gongyi Huang.(2016) An Empirical Bayes Method for Genotyping and SNP detection Using Multi-sample Next-generation Sequencing Data.

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