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A powerful procedure that controls the false discovery rate with directional information
Author(s) -
Tian Zhaoyang,
Liang Kun,
Li Pengfei
Publication year - 2021
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/biom.13277
Subject(s) - false discovery rate , multiple comparisons problem , computer science , statistical hypothesis testing , data mining , control (management) , value (mathematics) , statistics , computational biology , machine learning , artificial intelligence , mathematics , biology , gene , genetics
In many multiple testing applications in genetics, the signs of the test statistics provide useful directional information, such as whether genes are potentially up‐ or down‐regulated between two experimental conditions. However, most existing procedures that control the false discovery rate (FDR) are P ‐value based and ignore such directional information. We introduce a novel procedure, the signed‐knockoff procedure, to utilize the directional information and control the FDR in finite samples. We demonstrate the power advantage of our procedure through simulation studies and two real applications.