em_basic: Expectation Maximisation algorithm

In jsemple19/EMclassifieR: Classify DSMF data using the Expectation Maximisation algorithm

Expectation Maximisation algorithm

Description

Expectation Maximisation algorithm

Usage

em_basic(classes, priorProb, dataMatrix)

Arguments

classes	A matrix containing the classes to be optimised. c[i,j] is the expected methylation value or bincount value of class i at position j.
priorProb	A vector defining the prior probabilities of each class.
dataMatrix	A matrix containing the sample. dataMatrix [i,j] is the methylation value or bincount value of sample i at position j.

Value

A list of three items: 1) classes: a matrix with classes being optimised (class x position) 2) priorProb: a vector with the prior probabilities of each class 3) posteriorProb: a matrix of probabilites of each sample belonging to a particular class (samples x class)

jsemple19/EMclassifieR documentation built on Aug. 12, 2022, 2:57 p.m.