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A survey of best practices for RNA-seq data analysis

Overview of attention for article published in Genome Biology (Online Edition), January 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#20 of 2,734)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
1 news outlet
blogs
2 blogs
twitter
409 tweeters
facebook
10 Facebook pages
wikipedia
3 Wikipedia pages
googleplus
3 Google+ users
reddit
1 Redditor

Citations

dimensions_citation
380 Dimensions

Readers on

mendeley
4734 Mendeley
citeulike
30 CiteULike
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Title
A survey of best practices for RNA-seq data analysis
Published in
Genome Biology (Online Edition), January 2016
DOI 10.1186/s13059-016-0881-8
Pubmed ID
Authors

Ana Conesa, Pedro Madrigal, Sonia Tarazona, David Gomez-Cabrero, Alejandra Cervera, Andrew McPherson, Michał W Szcześniak, Daniel J Gaffney, Laura L Elo, Xuegong Zhang, Ali Mortazavi, Conesa, Ana, Madrigal, Pedro, Tarazona, Sonia, Gomez-Cabrero, David, Cervera, Alejandra, McPherson, Andrew, Szcześniak, Michał Wojciech, Gaffney, Daniel J, Elo, Laura L, Zhang, Xuegong, Mortazavi, Ali, Michał Wojciech Szcześniak, Daniel J. Gaffney, Laura L. Elo, Tarazona Campos, Sonia, Gómez Cabrero, David, Wojciech Szczesniak, Michal, Gaffney, Daniel J., Elo, Laura L., Sonia Tarazona Campos, David Gómez Cabrero, Michal Wojciech Szczesniak

Abstract

RNA-sequencing (RNA-seq) has a wide variety of applications, but no single analysis pipeline can be used in all cases. We review all of the major steps in RNA-seq data analysis, including experimental design, quality control, read alignment, quantification of gene and transcript levels, visualization, differential gene expression, alternative splicing, functional analysis, gene fusion detection and eQTL mapping. We highlight the challenges associated with each step. We discuss the analysis of small RNAs and the integration of RNA-seq with other functional genomics techniques. Finally, we discuss the outlook for novel technologies that are changing the state of the art in transcriptomics.

Twitter Demographics

The data shown below were collected from the profiles of 409 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 4,734 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4734 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 <1%
Unknown 4733 100%
Readers by discipline Count As %
Agricultural and Biological Sciences 1 <1%
Unknown 4733 100%

Attention Score in Context

This research output has an Altmetric Attention Score of 261. 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 21 September 2018.
All research outputs
#38,184
of 12,022,900 outputs
Outputs from Genome Biology (Online Edition)
#20
of 2,734 outputs
Outputs of similar age
#1,834
of 345,741 outputs
Outputs of similar age from Genome Biology (Online Edition)
#2
of 66 outputs
Altmetric has tracked 12,022,900 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,734 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.3. This one has done particularly well, scoring higher than 99% 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 345,741 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 99% of its contemporaries.
We're also able to compare this research output to 66 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.