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ROP: dumpster diving in RNA-sequencing to find the source of 1 trillion reads across diverse adult human tissues

Overview of attention for article published in Genome Biology (Online Edition), February 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)

Mentioned by

twitter
58 tweeters

Citations

dimensions_citation
30 Dimensions

Readers on

mendeley
81 Mendeley
citeulike
1 CiteULike
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Title
ROP: dumpster diving in RNA-sequencing to find the source of 1 trillion reads across diverse adult human tissues
Published in
Genome Biology (Online Edition), February 2018
DOI 10.1186/s13059-018-1403-7
Pubmed ID
Authors

Serghei Mangul, Harry Taegyun Yang, Nicolas Strauli, Franziska Gruhl, Hagit T. Porath, Kevin Hsieh, Linus Chen, Timothy Daley, Stephanie Christenson, Agata Wesolowska-Andersen, Roberto Spreafico, Cydney Rios, Celeste Eng, Andrew D. Smith, Ryan D. Hernandez, Roel A. Ophoff, Jose Rodriguez Santana, Erez Y. Levanon, Prescott G. Woodruff, Esteban Burchard, Max A. Seibold, Sagiv Shifman, Eleazar Eskin, Noah Zaitlen

Abstract

High-throughput RNA-sequencing (RNA-seq) technologies provide an unprecedented opportunity to explore the individual transcriptome. Unmapped reads are a large and often overlooked output of standard RNA-seq analyses. Here, we present Read Origin Protocol (ROP), a tool for discovering the source of all reads originating from complex RNA molecules. We apply ROP to samples across 2630 individuals from 54 diverse human tissues. Our approach can account for 99.9% of 1 trillion reads of various read length. Additionally, we use ROP to investigate the functional mechanisms underlying connections between the immune system, microbiome, and disease. ROP is freely available at https://github.com/smangul1/rop/wiki .

Twitter Demographics

The data shown below were collected from the profiles of 58 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 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 81 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 14 17%
Student > Ph. D. Student 13 16%
Researcher 13 16%
Student > Doctoral Student 7 9%
Student > Master 7 9%
Other 12 15%
Unknown 15 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 25 31%
Agricultural and Biological Sciences 18 22%
Medicine and Dentistry 9 11%
Computer Science 4 5%
Engineering 4 5%
Other 6 7%
Unknown 15 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 32. 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 12 August 2021.
All research outputs
#941,678
of 21,105,374 outputs
Outputs from Genome Biology (Online Edition)
#807
of 4,006 outputs
Outputs of similar age
#23,774
of 298,336 outputs
Outputs of similar age from Genome Biology (Online Edition)
#1
of 1 outputs
Altmetric has tracked 21,105,374 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,006 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.2. This one has done well, scoring higher than 79% 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 298,336 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 92% 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