Accurate and fast small \(p\)-value estimation for permutation tests in high-throughput genomic data analysis with the cross-entropy method
From MaRDI portal
Publication:6144029
DOI10.1515/sagmb-2021-0067zbMath1530.92167MaRDI QIDQ6144029
Weiping Shi, Yang Shi, Huining Kang, Mengqiao Wang, Ji-Hyun Lee, Hui Jiang
Publication date: 5 January 2024
Published in: Statistical Applications in Genetics and Molecular Biology (Search for Journal in Brave)
importance samplingMonte Carlo simulation\(p\)-valuepermutation testgenomic data analysisthe cross-entropy method
Applications of statistics to biology and medical sciences; meta analysis (62P10) Protein sequences, DNA sequences (92D20)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Improved cross-entropy method for estimation
- How accurate are the extremely small \(P\)-values used in genomic research: an evaluation of numerical libraries
- Bootstrap quantile estimation via importance resampling
- Optimization of computer simulation models with rare events
- General properties and estimation of conditional Bernoulli models
- The cross-entropy method for combinatorial and continuous optimization
- Adaptive resampling algorithms for estimating bootstrap distributions
- Significance analysis of microarrays applied to the ionizing radiation response
- Efficient p-value evaluation for resampling-based tests
- Handbook of Monte Carlo Methods
- Fast approximation of small p-values in permutation tests by partitioning the permutations
- How to Deal with the Curse of Dimensionality of Likelihood Ratios in Monte Carlo Simulation
- Weighted finite population sampling to maximize entropy
- Testing Statistical Hypotheses
- Introducing Monte Carlo Methods with R
This page was built for publication: Accurate and fast small \(p\)-value estimation for permutation tests in high-throughput genomic data analysis with the cross-entropy method