pValues

pValues-methods

pValues,npGSEAResultNorm-method

pValues,npGSEAResultBeta-method

pValues,npGSEAResultChiSq-method


 ~~ Methods for function <code>pValues</code> ~~


methods

Current gene set enrichment methods rely upon permutations
for inference.  These approaches are computationally expensive
and have minimum achievable p-values based on the number of
permutations, not on the actual observed statistics.  We have
derived three parametric approximations to the permutation
distributions of two gene set enrichment test statistics.  We
are able to reduce the computational burden and granularity
issues of permutation testing with our method, which is
implemented in this package. npGSEA calculates gene set
enrichment statistics and p-values without the computational
cost of permutations.  It is applicable in settings where one
or many gene sets are of interest.  There are also built-in
plotting functions to help users visualize results.

Jessica Larson

npGSEA

Permutation approximation methods for gene set enrichment
analysis (non-permutation GSEA)

pValues-methods function

<dl>
    <dt>
        <code>signature(x = "npGSEAResultNorm")</code>,<code>signature(x = "npGSEAResultBeta")</code>,
        <code>signature(x = "npGSEAResultChiSq")</code></dt><dd>These methods display the corresponding 
        p-values for the npGSEA analysis in the gene set in the given experiment.</dd> </dl> 

Methods

~~ Methods for function <code>pValues</code> ~~

pValues-methods: Methods for Function `pValues`

Description

Arguments

Methods

Examples