FDRestimation

FDRestimation estimates false discovery rates and adjusted p-values from p-values or z-scores in R to support statistical inference in large-scale biological studies.

Key Features:

• Distinguishing FDR and adjusted p-values: Explicitly differentiates between false discovery rates and adjusted p-values to clarify statistical interpretation.
• Null proportion estimation algorithms: Implements algorithms to estimate the null proportion of findings, a key component for accurate FDR estimation.
• Multiple adjustment methods: Supports a variety of adjustment methods for FDR estimation and control under different assumptions.
• Plotting functions: Provides plotting functions to visualize FDR estimates and related summary statistics.

Scientific Applications:

• Genomics: Applied to large-scale multiple testing in genomics.
• Proteomics: Applied to multiple hypothesis testing in proteomics.
• Other bioinformatics areas: Applied to high-throughput bioinformatics contexts that require FDR estimation and control.

Methodology:

Direct computation of FDRs and adjusted p-values from p-values or z-scores, estimation of the null proportion, and implementation of multiple adjustment algorithms that accommodate various assumptions about the data distribution.