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TRAPLINE: a standardized and automated pipeline for RNA sequencing data analysis, evaluation and annotation

Overview of attention for article published in BMC Bioinformatics, January 2016
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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 (91st percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

blogs
1 blog
twitter
15 X users
patent
2 patents
facebook
1 Facebook page

Citations

dimensions_citation
37 Dimensions

Readers on

mendeley
147 Mendeley
citeulike
3 CiteULike
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Title
TRAPLINE: a standardized and automated pipeline for RNA sequencing data analysis, evaluation and annotation
Published in
BMC Bioinformatics, January 2016
DOI 10.1186/s12859-015-0873-9
Pubmed ID
Authors

Markus Wolfien, Christian Rimmbach, Ulf Schmitz, Julia Jeannine Jung, Stefan Krebs, Gustav Steinhoff, Robert David, Olaf Wolkenhauer

Abstract

Technical advances in Next Generation Sequencing (NGS) provide a means to acquire deeper insights into cellular functions. The lack of standardized and automated methodologies poses a challenge for the analysis and interpretation of RNA sequencing data. We critically compare and evaluate state-of-the-art bioinformatics approaches and present a workflow that integrates the best performing data analysis, data evaluation and annotation methods in a Transparent, Reproducible and Automated PipeLINE (TRAPLINE) for RNA sequencing data processing (suitable for Illumina, SOLiD and Solexa). Comparative transcriptomics analyses with TRAPLINE result in a set of differentially expressed genes, their corresponding protein-protein interactions, splice variants, promoter activity, predicted miRNA-target interactions and files for single nucleotide polymorphism (SNP) calling. The obtained results are combined into a single file for downstream analysis such as network construction. We demonstrate the value of the proposed pipeline by characterizing the transcriptome of our recently described stem cell derived antibiotic selected cardiac bodies ('aCaBs'). TRAPLINE supports NGS-based research by providing a workflow that requires no bioinformatics skills, decreases the processing time of the analysis and works in the cloud. The pipeline is implemented in the biomedical research platform Galaxy and is freely accessible via www.sbi.uni-rostock.de/RNAseqTRAPLINE or the specific Galaxy manual page ( https://usegalaxy.org/u/mwolfien/p/trapline---manual ).

X Demographics

X Demographics

The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 147 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 4 3%
United States 2 1%
Switzerland 1 <1%
France 1 <1%
Netherlands 1 <1%
United Kingdom 1 <1%
Korea, Republic of 1 <1%
Unknown 136 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 49 33%
Student > Ph. D. Student 29 20%
Student > Master 14 10%
Student > Bachelor 10 7%
Student > Doctoral Student 7 5%
Other 24 16%
Unknown 14 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 46 31%
Biochemistry, Genetics and Molecular Biology 39 27%
Computer Science 20 14%
Medicine and Dentistry 7 5%
Engineering 3 2%
Other 10 7%
Unknown 22 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 13 February 2020.
All research outputs
#1,794,173
of 23,866,543 outputs
Outputs from BMC Bioinformatics
#390
of 7,454 outputs
Outputs of similar age
#32,152
of 398,842 outputs
Outputs of similar age from BMC Bioinformatics
#6
of 139 outputs
Altmetric has tracked 23,866,543 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,454 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 94% 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 398,842 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 139 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.