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Multiset Statistics for Gene Set Analysis
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DOI：10.1146/annurev-statistics-010814-020335.png)
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摘要
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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:
gene set enrichment
role model
statistical genomics
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论文数:
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CANCER RESEARCHOAAI
CANCER RESEARCHIF16.6
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