Description Details Author(s) References
An R package for computing gene and pathway p-values using the Adaptive Rank Truncated test. This package can be used to analyze pathways/genes based on a genetic association study, with either a continuous or a binary case-control outcome.
It is increasingly recognized that pathway analyses-a joint test of association between the outcome and a group of
single nucleotide polymorphisms (SNPs) within a biological pathway-could potentially complement single-SNP analysis and
provide additional insights for the genetic architecture of complex diseases.
Building upon existing P-value combining methods, we propose a class of highly flexible pathway analysis approaches based
on an adaptive rank truncated product statistic that can effectively combine evidence of associations over different SNPs and
genes within a pathway.
The statistical significance of the pathway-level test statistics is evaluated using a highly efficient permutation
algorithm that remains computationally feasible irrespective of the size of the pathway and complexity of the underlying test
statistics for summarizing SNP- and gene-level associations.
We demonstrate through simulation studies that a gene-based analysis that treats the underlying genes, as opposed to the underlying SNPs,
as the basic units for hypothesis testing, is a very robust and powerful approach to pathway-based association testing.
The function ARTP_pathway
is used to compute gene and pathway p-values provided that the observed and
permutation p-values for each SNP already exist in files. The input files required
for ARTP_pathway
can be obtained by calling the function runPermutations
.
Kai Yu <yuka@mail.nih.gov> and William Wheeler <wheelerb@imsweb.com>
Yu K, Li Q, Bergen AW, Pfeiffer RM, Rosenberg PS, Caporaso N, Kraft P, Chatterjee N Pathway analysis by adaptive combination of P-values Genet Epidemiol 33(8):700-9; 2009 Dec.
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