mlProjection: Maximum likelihood projection

In itikadi/EMOGEA: Error Modelled Gene Expression Analysis (EMOGEA) For RNA-Seq Measurements

Description

Function that computes the Maximum Likelihood PCA with equal row correlated errors.

Usage

mlProjection(
  expressionMatrix,
  errorCovarianceMatrix,
  numberOfComponents = 15,
  maxIterations = 2000,
  tolerance = 1e-10,
  verbose = TRUE
)

Arguments

expressionMatrix	The expression matrix organized as (*n* X *m*), *n* is the number of genes and *m* is the number of samples. You should use the expressionMatrix output of prepareData().
errorCovarianceMatrix	The inverse of the measurement errors, whose dimensions are (*n* X *n*). You should use the errorCovarianceMatrix output of prepareData().
numberOfComponents	The number of principal components estimated to be required to reconstruct the expression matrix without loss of generality.
maxIterations	The maximum number of iterations to peform during the computation of the Maximum Likelihood. Once the max iteration is reached, the algorithms stops.
tolerance	The termination tolerance for the computation of the Maximum Likelihood. Once the improvements made by Maximum Likelihood reach the tolerance, the algorithm stops.
verbose	Whether to display the information about the computation or not.

Value

A list consisting of U (principal components), S (eigenvalues) and V (loadings). The estimated matrix (estimatedMatrix) is given as t(U * S * t(V)).

Author(s)

Tobias K. Karakach, Federico Taverna

itikadi/EMOGEA documentation built on Dec. 20, 2021, 8:03 p.m.