A practical guide to methods controlling false discoveries in computational biology

A practical guide to methods controlling false discoveries in computational biology

Abstract Background In high-throughput studies, hundreds to millions of hypotheses are typically tested. Statistical methods that control the false discovery rate (FDR) have emerged as popular and powerful tools for error rate control. While classic FDR methods use only p values as input, more moder...

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Bibliographic Details
Main Authors: Keegan Korthauer, Patrick K. Kimes, Claire Duvallet, Alejandro Reyes, Ayshwarya Subramanian, Mingxiang Teng, Chinmay Shukla, Eric J. Alm, Stephanie C. Hicks
Format: Article
Language:English
Published: BMC 2019-06-01
Series:Genome Biology
Subjects:
Multiple hypothesis testing
False discovery rate
RNA-seq
ScRNA-seq
ChIP-seq
Microbiome
Online Access:http://link.springer.com/article/10.1186/s13059-019-1716-1

Internet

http://link.springer.com/article/10.1186/s13059-019-1716-1

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