mSAME: Association analysis using mutation-level association...
In Sun-lab/SAME: Somatic mutation Association test with Measurement Errors

View source: R/mSAME.R

mSAME

R Documentation

Association analysis using mutation-level association analysis.

Description

Association analysis using mutation-level association analysis.

Usage

mSAME(Y, X, O, D, A, out_type = "C", theta_init, mix_4bb, null = FALSE,
  d0 = 20, gamma0 = 1, gamma1 = 1, bounds = NULL, maxIt = 200,
  converged = 1e-06, reEst = 1, traceIt = 0, ...)

Arguments

`Y`	The response variable. Could be continuous or binary.
`X`	The design matrix. Intercept included.
`O`	A vector for the observed somatic mutation.
`D`	A vector for the total read-depth.
`A`	A vector for the number of alternative number matrix.
`out_type`	The outcome type, "C" for continous, "D" for dichotomous. Default is "C".
`theta_init`	The initail values of the parameters. Can be NULL.
`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.
`null`	Logical. Indicating the estimation using EM algorim under the null hypothesis or not. The default is FALSE.
`d0`	The minimum of the total read-depth for obtaining the observed somatic mutation value. The default value is 20.
`bounds`	Some parameters for the bounds in the EM algorithm. Can be NULL.
`converged`	The tolerance for the convergence. Default is 1e-6.
`gamm0`	The specificity of the somatic mutation. Default is 1.
`gamm1`	The sensitivity of the somatic mutation. Default is 1.
`maxIT`	The maximal number of the EM iteration times. Default is 200.