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Robust and adaptive non-parametric tests for detecting general distributional shifts in gene expression.

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第一作者： Fanding,Zhou

第一单位： Biostatistics Division, University of California, Berkeley, Berkeley, CA, USA.

作者： Fanding,Zhou ^[1] ; Alan J,Aw ^[2] ; Dan D,Erdmann-Pham ^[3] ; Jonathan,Fischer ^[4] ; Yun S,Song ^[5]

作者单位： Biostatistics Division, University of California, Berkeley, Berkeley, CA, USA. ^[1] Department of Statistics, University of California, Berkeley, Berkeley, CA, USA; Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA. ^[2] Department of Statistics, Stanford University, Stanford, CA, USA. ^[3] Department of Biostatistics, University of Florida, Gainesville, FL, USA. ^[4] Department of Statistics, University of California, Berkeley, Berkeley, CA, USA; Computer Science Division, University of California, Berkeley, Berkeley, CA, USA. Electronic address: yss@berkeley.edu. ^[5]

关键词 CP: Computational biology CP: Systems biology RNA-seq analysis aging differential dispersion differential expression pseudo-bulk single-cell analysis statistical hypothesis testing

主题词人类(Humans);基因表达谱(Gene Expression Profiling);统计学, 非参数(Statistics, Nonparametric);序列分析, RNA(Sequence Analysis, RNA);计算生物学(Computational Biology)

DOI 10.1016/j.crmeth.2025.101147

PMID 40902592

发布时间 2025-10-24

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