Data-adaptive test statistics represent a general methodology for performing multiple hypothesis testing on effects sizes while maintaining honest statistical inference when operating in high-dimensional settings (<doi here>). The utilities provided here extend the use of this general methodology to many common data analytic challenges that arise in modern computational and genomic biology.
|Author||Weixin Cai [aut, cre, cph], Nima Hejazi [aut], Alan Hubbard [ctb, ths]|
|Bioconductor views||DifferentialExpression DimensionReduction GeneExpression Genetics Microarray MultipleComparison Regression Sequencing|
|Maintainer||Weixin Cai <[email protected]>|
|Package repository||View on GitHub|
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