id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-103176-hfd8ur9a	Frost, H. Robert	Variance-adjusted Mahalanobis (VAM): a fast and accurate method for cell-specific gene set scoring	2020-02-19		.txt	text/plain	7407	305	46	Unfortunately, statistical and biological differences between single cell and bulk expression measurements make it challenging to use gene set testing methods originally developed for bulk tissue on scRNA-seq data and progress on single cell-specific methods has been limited. To address this challenge, we have developed a new gene set testing method, variance-adjusted Mahalanobis (VAM), that seamlessly integrates with the Seurat framework and is designed to accommodate the technical noise, sparsity and large sample sizes characteristic of scRNA-seq data. While these methods have proven effective for the analysis of bulk expression data, with GSVA and ssGSEA among the most popular techniques, the application of these methods to scRNA-seq data is limited by three main factors: poor classification performance in the presence of sparsity and technical noise, lack of inference support on the single cell level, and high computational cost (esp.	./cache/cord-103176-hfd8ur9a.txt	./txt/cord-103176-hfd8ur9a.txt