Reconstruction Set Test (RESET): A Computationally Efficient Method for Single Sample Gene Set Testing Based on Randomized Reduced Rank Reconstruction Error
Overview
Authors
Affiliations
We have developed a new, and analytically novel, single sample gene set testing method called Reconstruction Set Test (RESET). RESET quantifies gene set importance based on the ability of set genes to reconstruct values for all measured genes. RESET is realized using a computationally efficient randomized reduced rank reconstruction algorithm (available via the RESET R package on CRAN) that can effectively detect patterns of differential abundance and differential correlation for self-contained and competitive scenarios. As demonstrated using real and simulated scRNA-seq data, RESET provides superior performance at a lower computational cost relative to other single sample approaches.
Leveraging cell type-specificity for gene set analysis of single cell transcriptomics.
Frost H bioRxiv. 2024; .
PMID: 39386631 PMC: 11463668. DOI: 10.1101/2024.09.25.615040.
Li X, Fernandes B, Liu A, Chen J, Chen X, Zhao Z medRxiv. 2023; .
PMID: 37425929 PMC: 10327215. DOI: 10.1101/2023.06.19.23291621.