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Number of citations per year for the bioinformatics software tool RNASEQR

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chevron_left Read alignment Reference-based transcriptome assembly Spliced read alignment Variant detection chevron_right
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RNASEQR specifications


Unique identifier OMICS_01263
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Python
Computer skills Advanced
Stability Stable
Maintained Yes


No version available


  • person_outline Leslie Y. Chen

Publication for RNASEQR

RNASEQR citations


RNA Seq Identifies Key Reproductive Gene Expression Alterations in Response to Cadmium Exposure

Biomed Res Int
PMCID: 4058285
PMID: 24982889
DOI: 10.1155/2014/529271
call_split See protocol

[…] Raw data were mapped to the mouse reference genome (mm10 downloaded from UCSC) using TopHat (version 2.0.3) and RNASEQR (version 1.0.2) software, respectively [, ]. Prebuilt genomic indices were created by bowtie and provided to the alignment software for reads mapping. TopHat removes a few low-quality score re […]


Mining RNA–Seq Data for Infections and Contaminations

PLoS One
PMCID: 3760913
PMID: 24019895
DOI: 10.1371/journal.pone.0073071

[…] entification of the transcriptomic origin of each sequencing read (mapping), this has inspired the development of several novel RNA–seq mapping tools, e.g. TopHat and TopHat2 , MapSplice , RUM , and RNASEQR . While all of these rely on fast alignment algorithms such as Bowtie , they use different strategies to identify reads from exon–exon junctions, a problem unique to RNA–seq data. In general, […]


A Comprehensive Evaluation of Alignment Algorithms in the Context of RNA Seq

PLoS One
PMCID: 3530550
PMID: 23300661
DOI: 10.1371/journal.pone.0052403

[…] differ in their strategies for mapping reads crossing splice junctions or the use of only an alignment to the genome (e.g. TopHat, MapSplice and ContextMap) or also to the transcriptome (e.g. RUM and RNASEQR), all of these require specialized alignment algorithms to actually align the sequencing reads to the genome or transcriptome. For instance, RUM and RNASEQR start with read alignments to the […]


A context based approach to identify the most likely mapping for RNA seq experiments

BMC Bioinformatics
PMCID: 3358662
PMID: 22537048
DOI: 10.1186/1471-2105-13-S6-S9

[…] Subsequently, potential splice sites are annotated based on canonical splice signals and reads spanning these splice sites are identified. In contrast, two more recently published methods, RUM [] and RNASEQR [], start with read alignments to both the reference transcriptome and genome. Novel splice junctions are then identified by aligning unmapped reads to the genome using BLAT [] which determine […]

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RNASEQR institution(s)
Institute for Systems Biology, Seattle, WA, USA; Department of Neurosurgery, Chang Gung University College of Medicine and Memorial Hospital, Kwei-Shan, Taoyuan County, Taiwan, China; Department of Computer Science, National Tsing-Hua University, Hsinchu, Taiwan, China; Department of Computer Science and Information Engineering, Providence University, Taichung, Taiwan, China; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Luxembourg

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