myeloma_output

A dataset containing the results of pathfindR's active-subnetwork-oriented
enrichment workflow performed on the Mus musculus myeloma
differential expression dataset <code><a rd-options="" href="/link/myeloma_input?package=pathfindR&version=1.4.2" data-mini-rdoc="pathfindR::myeloma_input">myeloma_input</a></code>.
Generated on Nov 1, 2019.

datasets

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>.

Ege Ulgen

pathfindR

Enrichment Analysis Utilizing Active Subnetworks

Ozan Ozisik

myeloma_output function

A data frame with 18 rows and 8 columns:<dl class="dl-horizontal">
 <dt>ID</dt><dd>ID of the enriched term</dd>
 <dt>Term_Description</dt><dd>Description of the enriched term</dd>
 <dt>Fold_Enrichment</dt><dd>Fold enrichment value for the enriched term</dd>
 <dt>occurrence</dt><dd>the number of iterations that the given term was found to enriched over all iterations</dd>
 <dt>lowest_p</dt><dd>the lowest adjusted-p value of the given term over all iterations</dd>
 <dt>highest_p</dt><dd>the highest adjusted-p value of the given term over all iterations</dd>
 <dt>Up_regulated</dt><dd>the up-regulated genes in the input involved in the given term, comma-separated</dd>
 <dt>Down_regulated</dt><dd>the down-regulated genes in the input involved in the given term, comma-separated</dd>
</dl>

Format

A dataset containing the results of pathfindR's active-subnetwork-oriented
enrichment workflow performed on the Mus musculus myeloma
differential expression dataset <code><a rd-options='' href='myeloma_input'>myeloma_input</a></code>.
Generated on Nov 1, 2019.

Example Output for Myeloma Analysis (Mus Musculus) — myeloma_output

A data frame with 18 rows and 8 columns:<dl class='dl-horizontal'>
 <dt>ID</dt><dd>ID of the enriched term</dd>
 <dt>Term_Description</dt><dd>Description of the enriched term</dd>
 <dt>Fold_Enrichment</dt><dd>Fold enrichment value for the enriched term</dd>
 <dt>occurrence</dt><dd>the number of iterations that the given term was found to enriched over all iterations</dd>
 <dt>lowest_p</dt><dd>the lowest adjusted-p value of the given term over all iterations</dd>
 <dt>highest_p</dt><dd>the highest adjusted-p value of the given term over all iterations</dd>
 <dt>Up_regulated</dt><dd>the up-regulated genes in the input involved in the given term, comma-separated</dd>
 <dt>Down_regulated</dt><dd>the down-regulated genes in the input involved in the given term, comma-separated</dd>
</dl>

myeloma_output: Example Output for Myeloma Analysis (Mus Musculus)

Description

Usage

Arguments

Format

See Also