Abstract
AbstractWe describe a novel single sample pathway analysis method for cancer transcriptomics data namedtissue-adjusted pathway analysis of cancer(TPAC). The TPAC method leverages information about the normal tissue-specificity of human genes to compute a robust multivariate distance score that quantifies pathway dysregulation in each profiled tumor. Because the null distribution of the TPAC scores has an accurate gamma approximation, both population and sample-level inference is supported. As we demonstrate through an analysis of gene expression data from The Cancer Genome Atlas (TCGA), TPAC pathway scores are more strongly associated with both patient prognosis and tumor stage than the scores generated by existing single sample pathway analysis methods. An R package implementing the TPAC method can be found athttps://hrfrost.host.dartmouth.edu/TPAC.
Publisher
Cold Spring Harbor Laboratory
Cited by
2 articles.
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