Multivariate Pathway Enrichment Analysis
An integrative method of analyzing multi omics data that conducts enrichment analysis of annotated gene sets. 'ActivePathways' uses a statistical data fusion approach, rationalizes contributing evidence and highlights associated genes, improving systems-level understanding of cellular organization in health and disease.
- Add a geneset.filter option to activeDriverPW to filter the GMT by geneset size
- Add vignettes
- Export merge_p_values method
- Change column contribution method. Column contribution is now reported as the
log-fold-change when the column is excluded. ie, -log10(p_val_with_column / p_val_without_column)
- No longer raises an error if no significant terms are found and
is false. Instead returns an empty
data.table and issues a warning.
- Issue a warning if genes are filtered out for not being found in the background
- Change default p-value adjustment method to "holm"
- If return.all==FALSE, calculates columnContribution only for terms that will
returned. Speeds up runtime by roughly a factor of 2
- Add "none" option to p-value adjustment methods
- New implementation of orderedHypergeometric function which is several times faster.
- Fix Brown's method when all p-values in a column are the same
- Fix in orderedHypergeometric which added an extra NA to the
to small errors in the calculated p-value
- Fixed another bug in orderedHypergeometric which added an extra NA to the
complement in some cases, leading to small errors in the calculated p-value