On "Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates": Does a large number of tests obviate confidence intervals of the FDR?
David R. Bickel
Abstract
A previously proved theorem gives sufficient conditions for an estimator of the false discovery rate (FDR) to conservatively converge to the FDR with probability 1 as the number of hypothesis tests increases, even for small sample sizes. It does not follow that several thousand tests ensure that the estimator has moderate variance under those conditions. In fact, they can hold even if the test statistics have long-range correlations, which yield unacceptably wide confidence intervals, as observed in genomic data when there are 8 or 16 individuals (microarrays) per group. Thus, informative FDR estimation will include some measure of its reliability.
Create a lesson
Related papers
Homogeneity and heterogeneity of functional element composition of genome units across human and seven model organisms
Yanying Wu
Unlocking the Regulatory Genome by ARGUS: An Evidence-Constrained Agentic Framework for Interpreting Single Nucleotide Variants
Pratik Dutta, Matthew B. Obusan, Max Chao et al.
Truecell reproduces R Seurat's single-cell analysis outputs natively in the Python ecosystem
Nuzla Ismail, Shanika Amarasoma, Michelle Galeas-Pena et al.
Beyond the Transcriptome: Chromatin-Informed Prediction of Cell-State-Dependent Perturbation Responses
Jiafa Ruan, Chenyang He, Ruijie Quan et al.
HRPv2: an automated and enhanced method for full-length homology-based R-gene prediction
Giuseppe Andolfo, Thomas Holzweber, Juliane C. Dohm et al.
Tracing model-generated DNA with position-independent watermarking
Kimon Antonios Provatas1, Christos Galanopoulos, Ilias Georgakopoulos-Soares