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Article

Identification of population-level differentially expressed genes in one-phenotype data.

Bioinformatics (Oxford, England) - 1 Aug 2020

Xie Jiajing, Xu Yang, Chen Haifeng, Chi Meirong, He Jun, Li Meifeng, Liu Hui, Xia Jie, Guan Qingzhou, Guo Zheng, Yan Haidan

Abstract excerpt

MOTIVATION: For some specific tissues, such as the heart and brain, normal controls are difficult to obtain. Thus, studies with only a particular type of disease samples (one phenotype) cannot be analyzed using common methods, such as significance analysis of microarrays, edgeR and limma. The RankComp algorithm, which was mainly developed to identify individual-level differentially expressed genes (DEGs), can be...

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PMID: 32428201
DOI: 10.1093/bioinformatics/btaa523
PMCID: PMC7520039

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026. Manifest publication-graph-cohort-2026-09-06.1.

Source receipt: pubmed, retrieved 6 Sept 2026.

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