ArticleBioinformatics (Oxford, England)2023
Global FDR control across multiple RNAseq experiments.
Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Guidelines to Study Transcriptome Remodeling by Proteins Using Deep Sequencing (RNA-Seq).Methods in molecular biology (Clifton, N.J.) · 2027Article
- Machine learning and bioinformatics identify and validate membrane protein biomarkers for type 2 diabetes mellitus.Frontiers in endocrinology · 2026Article
- ARACRA: Automated RNA-seq Analysis for Chemical Risk Assessment.Computational and structural biotechnology journal · 2026Article
- Unique RNA Gene Expression Profile Is Seen in Chronic Non-Specific Low Back Pain.International journal of molecular sciences · 2025Article
- Changes in ferroptosis-related molecular expression in macrophages of community-acquired pneumonia patients and their associated with the disease progression.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2025Article
- Genome-wide identification of kiwifruit KBMC plant biology · 2024Article
- Exploring the Potential of Olfactory Receptor Circulating RNA Measurement for Preeclampsia Prediction and Its Linkage to Mild Gestational Hypothyroidism.International journal of molecular sciences · 2023Article
- Online multiple hypothesis testing.Statistical science : a review journal of the Institute of Mathematical Statistics · 2023Article
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Authors and funding
3 authors.
Funding
Abstract
motivationWhile classical approaches for controlling the false discovery rate (FDR) of RNA sequencing (RNAseq) experiments have been well described, modern research workflows and growing databases enable a new paradigm of controlling the FDR globally across RNAseq experiments in the past, present and future. The simplest analysis strategy that analyses each RNAseq experiment separately and applies an FDR correction method can lead to inflation of the overall FDR. We propose applying recently developed methodology for online multiple hypothesis testing to control the global FDR in a principled way across multiple RNAseq experiments.
resultsWe show that repeated application of classical repeated offline approaches has variable control of global FDR of RNAseq experiments over time. We demonstrate that the online FDR algorithms are a principled way to control FDR. Furthermore, in certain simulation scenarios, we observe empirically that online approaches have comparable power to repeated offline approaches. AVAILABILITY AND IMPLEMENTATION: The onlineFDR package is freely available at http://www.bioconductor.org/packages/onlineFDR. Additional code used for the simulation studies can be found at https://github.com/latlio/onlinefdr_rnaseq_simulation. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.