input_testing

the input data that pathfindR uses. The input must be a data
 frame with three columns:<ol>
<li>Gene Symbol (Gene Symbol)</li>
<li>Change value, e.g. log(fold change) (OPTIONAL)</li>
<li>p value, e.g. adjusted p value associated with differential expression</li>
</ol>

input

the p value threshold to use when filtering
the input data frame. Must a numeric value between 0 and 1. (default = 0.05)

p_val_threshold

Enrichment analysis enables researchers to uncover mechanisms
underlying a phenotype. However, conventional methods for enrichment
analysis do not take into account protein-protein interaction information,
resulting in incomplete conclusions. pathfindR is a tool for enrichment
analysis utilizing active subnetworks. The main function identifies active
subnetworks in a protein-protein interaction network using a user-provided
list of genes and associated p values. It then performs enrichment analyses
on the identified subnetworks, identifying enriched terms (i.e. pathways or,
more broadly, gene sets) that possibly underlie the phenotype of interest.
pathfindR also offers functionalities to cluster the enriched terms and
identify representative terms in each cluster, to score the enriched terms
per sample and to visualize analysis results. The enrichment, clustering and
other methods implemented in pathfindR are described in detail in
Ulgen E, Ozisik O, Sezerman OU. 2019. pathfindR: An R Package for
Comprehensive Identification of Enriched Pathways in Omics Data Through
Active Subnetworks. Front. Genet. <doi:10.3389/fgene.2019.00858>.

input_testing: Input Testing

Description

Usage

Arguments

Value

See Also

Examples