- p|value|free FDR control on high|throughput data from two conditions🔍
- Global FDR control across multiple RNAseq experiments🔍
- Exaggerated false positives by popular differential expression ...🔍
- False Discovery Rate🔍
- Powerful and interpretable control of false discoveries in two|group ...🔍
- Statistical and Computational Methods for Comparing High ...🔍
- A selective inference approach for false discovery rate control using ...🔍
- Enhancing Rigor in Computational Methods for Biological Data ...🔍
p|value|free FDR control on high|throughput data from two conditions
Clipper: p-value-free FDR control on high-throughput data from two ...
The most widely used criterion to ensure the analysis reliability is the false discovery rate (FDR), which is primarily controlled based on p- ...
p-value-free FDR control on high-throughput data from two conditions
Clipper is a general statistical framework for FDR control without relying on p-values or specific data distributions. Clipper outperforms ...
Clipper: p-value-free FDR control on high-throughput data from two ...
Clipper: p-value-free FDR control on high-throughput data from two conditions. Jingyi Jessica Li. Joint work with Xinzhou Ge and Yiling Elaine Chen (Ph.D ...
p-value-free FDR control on high-throughput data from two conditions
Clipper: p-value-free FDR control on high-throughput data from two conditions. Jingyi Jessica Li. High-throughput biological data analysis commonly involves ...
p-value-free FDR control on high-throughput data from two conditions
Existing bioinformatics tools primarily control the FDR based on p-values. However, obtaining valid p-values relies on either reasonable ...
p-value-free FDR control on high-throughput data from two conditions
High-throughput biological data analysis commonly involves identifying “interesting” features (e.g., genes, genomic regions, and proteins), ...
p-value-free FDR control on high-throughput data from two conditions
High-throughput biological data analysis commonly involves identifying features such as genes, genomic regions, and proteins, whose values differ between ...
Clipper: p-value-free FDR control on high-throughput data from two ...
The most widely-used criterion to ensure the analysis reliability is the false discovery rate (FDR), which is primarily controlled based on p- ...
p-value-free FDR control on high-throughput data from two conditions
However, obtaining valid p-values relies on either reasonable assumptions of data distribution or large numbers of replicates under both conditions. Clipper is ...
Clipper: p-value-free FDR control on high-throughput data from two ...
High-throughput biological data analysis commonly involves identifying features such as genes, genomic regions, and proteins, whose values ...
p-value-free FDR control on high-throughput data from two conditions
bioRxiv link: https://doi.org/10.1101/2020.11.19.390773.
p-value-free FDR control on high-throughput data from two conditions
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, ...
Global FDR control across multiple RNAseq experiments - PMC
Zrnic et al. (2020) have shown theoretical guarantees that FDR will be controlled across all p-values, assuming p-values are independent.
Exaggerated false positives by popular differential expression ...
Clipper: p-value-free FDR control on high-throughput data from two conditions. Genome Biol. 2021;22:288. Article PubMed Google Scholar. Li Y ...
An FDR of 5% means that, among all features called significant, 5% of these are truly null. Just as we set alpha as a threshold for the p-value to control the ...
Clipper: A General Statistical Framework for P-Value-Free FDR ...
The most famous Benjamini-Hochberg procedure for FDR control requires valid high-resolution p-values, which are, however, often hardly achievable because of ...
Powerful and interpretable control of false discoveries in two-group ...
The standard approach for statistical inference in differential expression (DE) analyses is to control the false discovery rate (FDR).
Statistical and Computational Methods for Comparing High ...
Existing bioinformatics tools primarily control the FDR based on p-values. However, obtaining valid p-values relies on either reasonable assumptions of data ...
A selective inference approach for false discovery rate control using ...
One approach is to control the false discovery rate (FDR), and a recent selective inference method for controlling FDR, adaptive P-value thresholding (AdaPT), ...
Enhancing Rigor in Computational Methods for Biological Data ...
Clipper: p-value-free FDR control on high-throughput data from two conditions. Genome. Biology 22, 288 (2021). [9] Riaz, N. et al. Tumor and microenvironment ...