mSAME: Association analysis using mutation-level association...

Description Usage Arguments Value

Description

Association analysis using mutation-level association analysis.

Usage

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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.

Value

A list containing the output of the EM algorithm.

Theta
theta
LogLik
logLik
it

Sun-lab/SAME documentation built on May 30, 2019, 11:48 p.m.