DEVarSelect: Feature selection for reference-free deconvolution using...
In ziyili20/TOAST: Tools for the analysis of heterogeneous tissues

DEVarSelect

R Documentation

Feature selection for reference-free deconvolution using cross-cell type differential analysis

Description

This function selects cross-cell type differential features for reference-free deconvolution.

Usage

DEVarSelect(Y_raw, Prop0, nMarker, bound_negative)

Arguments

`Y_raw`	A data matrix containing P features and N samples; or a SummarizedExperiment object.
`Prop0`	A N by K proportion matrix with K as number of cell types.
`nMarker`	Number of markers selected.
`bound_negative`	Whether to bound all negative parameter estimators to zero.

Value

Selected markers using cross-cell type differential analysis.

Author(s)

Ziyi Li <zli16@mdanderson.org>

References

Ziyi Li, Zhijin Wu, Peng Jin, Hao Wu. "Dissecting differential signals in high-throughput data from complex tissues."

Examples

Y_raw <- matrix(runif(5000*20, 0, 1), 5000, 20)
tmp <- matrix(runif(20*4), 20, 4)
Prop0 <- sweep(tmp, 1, rowSums(tmp), "/")
varlist <- DEVarSelect(Y_raw, Prop0,
                       nMarker=1000,
                       bound_negative=FALSE)

ziyili20/TOAST documentation built on Aug. 28, 2022, 11:28 a.m.