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Annual Review of Statistics and Its Application

Volume 2, 2015

Multiset Statistics for Gene Set Analysis

Abstract

An important data analysis task in statistical genomics involves the integration of genome-wide gene-level measurements with preexisting data on the same genes. A wide variety of statistical methodologies and computational tools have been developed for this general task. We emphasize one particular distinction among methodologies, namely whether they process gene sets one at a time (uniset) or simultaneously via some multiset technique. Owing to the complexity of collections of gene sets, the multiset approach offers some advantages, as it naturally accommodates set-size variations and among-set overlaps. However, this approach presents both computational and inferential challenges. After reviewing some statistical issues that arise in uniset analysis, we examine two model-based multiset methods for gene list data.

Keyword(s): gene set enrichment, role model, statistical genomics
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/content/journals/10.1146/annurev-statistics-010814-020335
2015-04-10
2024-04-29
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/content/journals/10.1146/annurev-statistics-010814-020335
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Multiset Statistics for Gene Set Analysis
Annual Review of Statistics and Its Application 2, 95 (2015); https://doi.org/10.1146/annurev-statistics-010814-020335
/content/journals/10.1146/annurev-statistics-010814-020335
/content/journals/10.1146/annurev-statistics-010814-020335
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  • Article Type: Review Article

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