sigSAME: Compute the likelihood for the observed somatic mutation and...

In Sun-lab/SAME: Somatic mutation Association test with Measurement Errors

Compute the likelihood for the observed somatic mutation and the read-depth data for gSAME. It can significantly reduce computational time for assication analysis between one gene-level mutation and lots of outcomes.

Description

Compute the likelihood for the observed somatic mutation and the read-depth data for gSAME. It can significantly reduce computational time for assication analysis between one gene-level mutation and lots of outcomes.

Usage

sigSAME(O, D, A, d0 = 20, min_altcount = 1, spesen = NULL,
  mix_4bb = NULL, mix_2bb = NULL)

Arguments

O	A matrix for the observed somatic mutation.
D	A matrix for the total read-depth.
A	A matrix for the number of alternative number matrix.
d0	The minimum of the total read-depth for obtaining the observed somatic mutation value. The default value is 20.
min_altcount	The mimimum of the number of alternative reads that the somatic mutation could acutally orrur. The default value is 1.
spesen	A dataframe specifying the specificity and sensitivity for all the somatic mutations.
mix_4bb	A dataframe indicating the parameters of four beta-binomial distributions depending on the values of the observed somatic mutaton and the true somatic mutation when the read-depth is high.
mix_2bb	A dataframe indicating the parameters of two beta-binomial distributions depending on the true value of the somatic mutation when the read-depth is low.

Value

A matrix with the likelihood of O, D, A conditioning on the true value of the somatic mutation (S=0/1) for all the samples.

Sun-lab/SAME documentation built on Jan. 27, 2024, 6:48 p.m.