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hypeR: an R package for geneset enrichment workflows.

Anthony Federico1,2, Stefano Monti1,2

  • 1Bioinformatics Department, Boston University, Boston, MA 02118, USA.

Bioinformatics (Oxford, England)
|September 10, 2019
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Summary
This summary is machine-generated.

This study introduces hypeR, a flexible R package for geneset enrichment analysis. It offers comprehensive tools for annotating high-throughput sequencing data, addressing limitations of existing methods for diverse research needs.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Geneset enrichment analysis is crucial for interpreting high-throughput sequencing data.
  • Current tools lack the flexibility needed for complex, multi-experiment analyses.
  • Researchers require adaptable solutions for diverse annotation challenges.

Purpose of the Study:

  • To develop a comprehensive R package for streamlined geneset enrichment workflows.
  • To provide enhanced flexibility and novel features for data annotation.
  • To create a versatile tool for a broad range of users and applications.

Main Methods:

  • Development of a comprehensive R package named hypeR.
  • Implementation of multiple enrichment and visualization methods.
  • Inclusion of hierarchical geneset analysis and markdown reporting.

Main Results:

  • hypeR offers a unified solution for geneset enrichment analysis.
  • The package provides advanced features like hierarchical analysis and reporting.
  • It enhances flexibility for analyzing multiple gene signatures across experiments.

Conclusions:

  • hypeR addresses the limitations of existing geneset enrichment tools.
  • The package serves as a one-stop solution for researchers in genomics and bioinformatics.
  • It facilitates efficient and flexible annotation of sequencing data.