ArticleGenome biology2021
Clipper: p-value-free FDR control on high-throughput data from two conditions.
Article in Genome biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
33 citing papers in PubMed, 1 synthesis or guideline pooled it.
- ClusterDE: A Statistical Software Package for Removing Double-Dipping Bias in Post-Clustering Differential Expression Analysis.Journal of computational biology : a journal of computational molecular cell biology · 2026Guideline
- PRIME-BSPre: a genome-wide protein-RNA binding sites prediction method based on templates.BMC genomics · 2026Article
- eIF4E assembly intobioRxiv : the preprint server for biology · 2025Article
- Robust and adaptive non-parametric tests for detecting general distributional shifts in gene expression.Cell reports methods · 2025Article
- Explicit Scale Simulation for analysis of RNA-sequencing count data with ALDEx2.NAR genomics and bioinformatics · 2025Article
- ClipperQTL: ultrafast and powerful eGene identification method.Genome biology · 2025Article
- Article
- reg-eQTL: Integrating transcription factor effects to unveil regulatory variants.American journal of human genetics · 2025Article
- Categorization of 34 computational methods to detect spatially variable genes from spatially resolved transcriptomics data.Nature communications · 2025Review
- DNA methylation profiling at base-pair resolution reveals unique epigenetic features of early-onset colorectal cancer in underrepresented populations.Clinical epigenetics · 2025Article
- Synthetic control removes spurious discoveries from double dipping in single-cell and spatial transcriptomics data analyses.bioRxiv : the preprint server for biology · 2024Article
- Article
- TWAS-GKF: a novel method for causal gene identification in transcriptome-wide association studies with knockoff inference.Bioinformatics (Oxford, England) · 2024Article
- APIR: Aggregating Universal Proteomics Database Search Algorithms for Peptide Identification with FDR Control.Genomics, proteomics & bioinformatics · 2024Article
- Article
- Article
- Preserving Pure Siamese Crocodile Populations: A Comprehensive Approach Using Multi-Genetic Tools.Biology · 2023Article
- How the Monty Hall problem is similar to the false discovery rate in high-throughput data analysis.Nature biotechnology · 2023Article
- Functional characterization of age-dependent p16 epimutation reveals biological drivers and therapeutic targets for colorectal cancer.Journal of experimental & clinical cancer research : CR · 2023Article
- The systematic comparison between Gaussian mirror and Model-X knockoff models.Scientific reports · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
High-throughput biological data analysis commonly involves identifying features such as genes, genomic regions, and proteins, whose values differ between two conditions, from numerous features measured simultaneously. The most widely used criterion to ensure the analysis reliability is the false discovery rate (FDR), which is primarily controlled based on p-values. However, obtaining valid p-values relies on either reasonable assumptions of data distribution or large numbers of replicates under both conditions. Clipper is a general statistical framework for FDR control without relying on p-values or specific data distributions. Clipper outperforms existing methods for a broad range of applications in high-throughput data analysis.
Indexed as
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.