Header

UZH-Logo

Maintenance Infos

Rcount: simple and flexible RNA-Seq read counting


Schmid, Marc W; Grossniklaus, Ueli (2015). Rcount: simple and flexible RNA-Seq read counting. Bioinformatics, 31(3):436-437.

Abstract

SUMMARY: Analysis of differential gene expression by RNA sequencing (RNA-Seq) is frequently done using feature counts, i.e. the number of reads mapping to a gene. However, commonly used count algorithms (e.g. HTSeq) do not address the problem of reads aligning with multiple locations in the genome (multireads) or reads aligning with positions where two or more genes overlap (ambiguous reads). Rcount specifically addresses these issues. Furthermore, Rcount allows the user to assign priorities to certain feature types (e.g. higher priority for protein-coding genes compared to rRNA-coding genes) or to add flanking regions. Availability and implementation: Rcount provides a fast and easy-to-use graphical user interface requiring no command line or programming skills. It is implemented in C++ using the SeqAn (www.seqan.de) and the Qt libraries (qt-project.org). Source code and 64 bit binaries for (Ubuntu) Linux, Windows (7) and MacOSX are released under the GPLv3 license and are freely available on github.com/MWSchmid/Rcount. CONTACT marcschmid@gmx.ch SUPPLEMENTARY INFORMATION: Test data, genome annotation files, useful Python and R scripts and a step-by-step user guide (including run-time and memory usage tests) are available on github.com/MWSchmid/Rcount.

Abstract

SUMMARY: Analysis of differential gene expression by RNA sequencing (RNA-Seq) is frequently done using feature counts, i.e. the number of reads mapping to a gene. However, commonly used count algorithms (e.g. HTSeq) do not address the problem of reads aligning with multiple locations in the genome (multireads) or reads aligning with positions where two or more genes overlap (ambiguous reads). Rcount specifically addresses these issues. Furthermore, Rcount allows the user to assign priorities to certain feature types (e.g. higher priority for protein-coding genes compared to rRNA-coding genes) or to add flanking regions. Availability and implementation: Rcount provides a fast and easy-to-use graphical user interface requiring no command line or programming skills. It is implemented in C++ using the SeqAn (www.seqan.de) and the Qt libraries (qt-project.org). Source code and 64 bit binaries for (Ubuntu) Linux, Windows (7) and MacOSX are released under the GPLv3 license and are freely available on github.com/MWSchmid/Rcount. CONTACT marcschmid@gmx.ch SUPPLEMENTARY INFORMATION: Test data, genome annotation files, useful Python and R scripts and a step-by-step user guide (including run-time and memory usage tests) are available on github.com/MWSchmid/Rcount.

Statistics

Citations

Dimensions.ai Metrics
26 citations in Web of Science®
28 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

107 downloads since deposited on 12 Mar 2015
35 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Department of Plant and Microbial Biology
07 Faculty of Science > Zurich-Basel Plant Science Center
Dewey Decimal Classification:580 Plants (Botany)
Scopus Subject Areas:Physical Sciences > Statistics and Probability
Life Sciences > Biochemistry
Life Sciences > Molecular Biology
Physical Sciences > Computer Science Applications
Physical Sciences > Computational Theory and Mathematics
Physical Sciences > Computational Mathematics
Language:English
Date:2015
Deposited On:12 Mar 2015 07:48
Last Modified:26 Jan 2022 05:14
Publisher:Oxford University Press
ISSN:1367-4803
OA Status:Hybrid
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1093/bioinformatics/btu680
PubMed ID:25322836
  • Content: Published Version
  • Language: English
  • Description: Nationallizenz 142-005