GAPGOM: GAPGOM (novel Gene Annotation Prediction and other GO Metrics)

Collection of various measures and tools for lncRNA annotation prediction put inside a redistributable R package. The package contains two main algorithms; lncRNA2GOA and TopoICSim. lncRNA2GOA tries to annotate novel genes (in this specific case lncRNAs) by using various correlation/geometric scoring methods on correlated expression data. After correlating/scoring, the results are annotated and enriched. TopoICSim is a topologically based method, that compares gene similarity based on the topology of the GO DAG by information content (IC) between GO terms.

Package details

AuthorRezvan Ehsani [aut, cre], Casper van Mourik [aut], Finn Drabløs [aut]
Bioconductor views GO GeneExpression GenePrediction
MaintainerRezvan Ehsani <rezvanehsani74@gmail.com>
LicenseMIT + file LICENSE
Version1.6.0
URL https://github.com/Berghopper/GAPGOM/
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("GAPGOM")

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GAPGOM documentation built on Nov. 8, 2020, 8:08 p.m.