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Related Experiment Video

Updated: Apr 22, 2026

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

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Rcount: simple and flexible RNA-Seq read counting.

Marc W Schmid¹, Ueli Grossniklaus¹

¹Institute of Plant Biology and Zürich-Basel Plant Science Center, University of Zurich, 8008 Zürich, Switzerland.

Bioinformatics (Oxford, England)

|October 18, 2014

Summary

This summary is machine-generated.

Rcount is a new tool that accurately counts gene expression from RNA sequencing data by addressing issues with multi- and ambiguous reads. It offers a user-friendly interface for precise gene expression analysis.

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Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

RNA sequencing (RNA-Seq) is crucial for analyzing gene expression.
Existing count algorithms struggle with multi- and ambiguous reads.
Accurate gene counting is essential for reliable differential gene expression analysis.

Purpose of the Study:

Introduce Rcount, a novel tool for accurate gene expression quantification.
Address limitations of current RNA-Seq count algorithms.
Provide a user-friendly solution for handling multi- and ambiguous reads.

Main Methods:

Rcount utilizes C++ with SeqAn and Qt libraries for implementation.
Features a graphical user interface (GUI) for ease of use.
Handles multi- and ambiguous reads, and allows feature type prioritization.

Main Results:

Rcount specifically addresses multi- and ambiguous reads in RNA-Seq analysis.
Enables prioritization of gene features (e.g., protein-coding vs. rRNA).
Offers flexibility by allowing the addition of flanking regions.

Conclusions:

Rcount provides a robust solution for accurate gene counting in RNA-Seq.
Improves differential gene expression analysis by resolving read assignment ambiguities.
Offers a fast, easy-to-use, and freely available tool for researchers.