GetFractions.Abbas: Constrained regression method implemented in Abbas et al.,...

In IOBR/IOBR: Immune Oncology Biological Research

Constrained regression method implemented in Abbas et al., 2009

Description

This function implements a constrained regression approach described by Abbas et al. in their 2009 paper. It is designed to estimate the proportions of immune cell types within a mixed cancer tissue sample based on gene expression data. The method iteratively adjusts the regression coefficients to ensure they are non-negative, which corresponds to realistic proportions of cell types.

Usage

GetFractions.Abbas(XX, YY, w = NA)

Arguments

XX	Matrix representing immune expression data with genes as rows and cell types as columns.
YY	Vector representing cancer expression data with gene expression levels.
w	Optional vector of weights for the regression, default is NA which means no weights are applied.

Value

A vector with non-negative coefficients representing the proportions of each cell type in the input expression data.

Examples

# Generate some example data
XX <- matrix(runif(100), nrow=10, ncol=10)
colnames(XX) <- paste("CellType", 1:10, sep="")
YY <- runif(10)

# Apply the Abbas constrained regression method
results <- GetFractions.Abbas(XX, YY)
print(results)

IOBR/IOBR documentation built on Sept. 9, 2024, 8:36 p.m.