id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
dv13zs28s33	Martin P. Barron	Statistical Machine Learning for Single-Cell RNA-Sequencing Data: Sparse Clustering for Cell Type Identification and Confounding Factor Removal	1904		.txt	text/plain	703	22	43	SparseDC is applicable to any situation where the simultaneous analysis of multiple populations consisting of independent observations is undertaken, such as examining data on individuals from different cities or countries, or stock market data taken from an index at different periods of time. Data coming from scRNA-seq experiments typically contain 100-10,000 cells and measurements for about 20,000-50,000 genes, this leads to a large \ extit{p} small \ extit{n} problem, leading to issues such as conventional clustering algorithms being ineffective due to the curse of dimensionality.	cache/dv13zs28s33.txt	txt/dv13zs28s33.txt