MetaGSCA systematically assesses the coexpression disturbance of a gene set by pooling the results from individual studies. A nonparametric approach named GSNCA (Rahmatallah 2014, Bioinformatics) is used to test whether the gene set is differentially co-expresssed between the two conditions, and a permutation test p-value is computed. Bootstrapping is used to construct confidence intervals of p-values. Meta-analysis is offered through two options: random-intercept logistic regression model and the inverse variance method. Lastly, a pathway crosstalk network is delineated based on the meta-analysis result outputted from the prior steps.
Package details |
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Bioconductor views | DifferentialExpression Software StatisticalMethod |
Maintainer | |
License | GPL (>= 2) |
Version | 0.99.6 |
Package repository | View on GitHub |
Installation |
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