COT: an efficient Python tool for detecting marker genes among many subtypes
作者： Georgia Saylor , David M. Herrington , Jennifer E. Van Eyk , Sarah J. Parker , Lulu Chen
DOI: 10.1101/2021.01.10.426146
关键词:
摘要: Abstract We develop an accurate and efficient method to detect marker genes among many subtypes using subtype-enriched expression profiles. implement a Cosine based One-sample Test (COT) Python software that is easy use applicable multi-omics data. demonstrate the performance utility of COT on gene proteomics data acquired from tissue or cell subtypes. Formulated as one-sample test with similarity statistic in scatter space, detected de novo will allow biologists perform more comprehensive unbiased molecular characterization, deconvolution classification complex
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