A metric for evaluating biological information in gene sets and its application to identify co-expressed gene clusters in PBMC

Volume: 17, Issue: 10, Pages: e1009459 - e1009459
Published: Oct 6, 2021
Abstract
Recent technological advances have made the gathering of comprehensive gene expression datasets a commodity. This has shifted the limiting step of transcriptomic studies from the accumulation of data to their analyses and interpretation. The main problem in analyzing transcriptomics data is that the number of independent samples is typically much lower (<100) than the number of genes whose expression is quantified (typically >14,000). To...
Paper Details
Title
A metric for evaluating biological information in gene sets and its application to identify co-expressed gene clusters in PBMC
Published Date
Oct 6, 2021
Volume
17
Issue
10
Pages
e1009459 - e1009459
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