Monte Carlo null models for genomic data

DOI10.1214/14-STS484zbMath1332.62411arXiv1404.5970OpenAlexW2025893165MaRDI QIDQ254411

Lars Holden, Geir Kjetil Sandve, Egil Ferkingstad

Publication date: 8 March 2016

Published in: Statistical Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1404.5970

zbMATH Keywords

hypothesis testingMonte Carlo methodsgenomics

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Hypothesis testing in multivariate analysis (62H15) Genetics and epigenetics (92D10)

Related Items (2)

ROhAN: row-order agnostic null models for statistically-sound knowledge discovery ⋮ Monte Carlo null models for genomic data

Uses Software

• R
• MCFDR
• TRANSFAC
• CisModule

Cites Work

• Unnamed Item
• Unnamed Item
• Monte Carlo null models for genomic data
• Subsampling methods for genomic inference
• A statistical significance testing approach to mining the most informative set of patterns
• The second-order analysis of stationary point processes
• A Direct Approach to False Discovery Rates
• Testing Statistical Hypotheses
• Estimating the Proportion of True Null Hypotheses, with application to DNA Microarray Data
• Large-Scale Simultaneous Hypothesis Testing

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