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ContextMap 2: fast and accurate context-based RNA-seq mapping

Overview of attention for article published in BMC Bioinformatics, April 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)

Mentioned by

blogs
1 blog
twitter
7 tweeters

Citations

dimensions_citation
40 Dimensions

Readers on

mendeley
68 Mendeley
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Title
ContextMap 2: fast and accurate context-based RNA-seq mapping
Published in
BMC Bioinformatics, April 2015
DOI 10.1186/s12859-015-0557-5
Pubmed ID
Authors

Thomas Bonfert, Evelyn Kirner, Gergely Csaba, Ralf Zimmer, Caroline C Friedel

Abstract

Mapping of short sequencing reads is a crucial step in the analysis of RNA sequencing (RNA-seq) data. ContextMap is an RNA-seq mapping algorithm that uses a context-based approach to identify the best alignment for each read and allows parallel mapping against several reference genomes. In this article, we present ContextMap 2, a new and improved version of ContextMap. Its key novel features are: (i) a plug-in structure that allows easily integrating novel short read alignment programs with improved accuracy and runtime; (ii) context-based identification of insertions and deletions (indels); (iii) mapping of reads spanning an arbitrary number of exons and indels. ContextMap 2 using Bowtie, Bowtie 2 or BWA was evaluated on both simulated and real-life data from the recently published RGASP study. We show that ContextMap 2 generally combines similar or higher recall compared to other state-of-the-art approaches with significantly higher precision in read placement and junction and indel prediction. Furthermore, runtime was significantly lower than for the best competing approaches. ContextMap 2 is freely available at http://www.bio.ifi.lmu.de/ContextMap .

Twitter Demographics

The data shown below were collected from the profiles of 7 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 6%
France 1 1%
Germany 1 1%
Japan 1 1%
Brazil 1 1%
Unknown 60 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 26%
Student > Ph. D. Student 15 22%
Student > Master 9 13%
Student > Bachelor 7 10%
Professor 4 6%
Other 10 15%
Unknown 5 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 43%
Biochemistry, Genetics and Molecular Biology 14 21%
Computer Science 8 12%
Engineering 4 6%
Immunology and Microbiology 2 3%
Other 5 7%
Unknown 6 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 May 2015.
All research outputs
#2,515,359
of 19,211,930 outputs
Outputs from BMC Bioinformatics
#948
of 6,554 outputs
Outputs of similar age
#37,314
of 239,671 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 1 outputs
Altmetric has tracked 19,211,930 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,554 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has done well, scoring higher than 85% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 239,671 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them