Pathway and gene level association test using raw data or summary statistics.
|License:||GPL-2 | GPL-3|
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.
The main functions in this package are
sARTP when only summary level data are available,
rARTP when genotype data are available, and
warm.start for computing gene and pathway p-values when previously save information is available.
Han Zhang, Bill Wheeler, Kai Yu, Yifan Yang
Maintainer: Han Zhang <[email protected]>
Zhang H, Wheeler W, Hyland LP, Yang Y, Shi J, Chatterjee N, Yu K. (2016) A powerful procedure for pathway-based meta-analysis using summary statistics identifies 43 pathways associated with type II diabetes in European populations. PLoS Genetics 12(6): e1006122
Yu K, Li Q, Bergen AW, Pfeiffer RM, Rosenberg PS, Caporaso N, Kraft P, Chatterjee N. (2009) Pathway analysis by adaptive combination of P-values. Genet Epidemiol 33(8): 700 - 709
Zhang H, Shi J, Liang F, Wheeler W, Stolzenberg-Solomon R, Yu K. (2014) A fast multilocus test with adaptive SNP selection for large-scale genetic association studies. European Journal of Human Genetics 22: 696 - 702
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.