It lists the supported GSEA methods. Since EGSEA base methods are implemented in the Bioconductor project, the most recent version of each individual method is always used.
These methods include:
ora, globaltest, plage, safe, zscore,
gage, ssgsea, roast, fry, padog,
camera and gsva.
ora, gage, camera and
gsva methods depend on a competitive null
hypothesis while the remaining seven methods are based on a self-contained hypothesis.
Conveniently, EGSEA is not limited to these twelve
GSE methods and new GSE tests can be easily integrated into the framework.
Note: the execution time of base methods can vary depending on the size of gene set collections, number of samples, number of genes and number of contrasts. When a gene set collection of around 200 gene sets was tested on a dataset of 17,500 genes, 8 samples and 2 contrasts, the execution time of base methods in ascending order was as follows:
globaltest; safe; gage; gsva; zscore; plage; fry; camera; ora; ssgsea; padog. When the
same dataset was tested on a large gene set collection of 3,700 gene sets, the execution
time of base methods in ascending order was as follows:
globaltest; camera; fry; zscore; plage; safe; gsva; ora; gage; padog; ssgsea. Apparently, the
size of gene set collection plays a key role in the execution time of most of the base
methods. The reduction rate of execution time between the large and small gene set
collections varied between 18% and 88%.
camera, fry, plage, zscore and
ora showed the least
reduction rate of execution time. As a result, there is no guarantee that a single combination
of base methods would run faster than other combinations. It is worth mentioning that
our simulation results showed that the increasing number of base methods in the EGSEA
analysis is desirable to achieve high performance.
It returns a character vector of supported GSE methods.
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