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Nanoblot: an R-package for visualization of RNA isoforms from long-read RNA-sequencing data

Overview of attention for article published in RNA, May 2023
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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 (#41 of 3,191)
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

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Title
Nanoblot: an R-package for visualization of RNA isoforms from long-read RNA-sequencing data
Published in
RNA, May 2023
DOI 10.1261/rna.079505.122
Pubmed ID
Authors

Samuel DeMario, Kevin Xu, Kevin He, Guillaume F. Chanfreau

Abstract

RT-PCR and northern blots have long been used to study RNA isoforms usage for single genes. Recently, advancements in long read sequencing have yielded unprecedented information about the usage and abundance of these RNA isoforms. However, visualization of long-read sequencing data remains challenging due to the high information density. To alleviate these issues we have developed NanoBlot, an open-source, R-package, which generates northern blot and RT-PCR-like images from long-read sequencing data. NanoBlot requires aligned, positionally sorted and indexed BAM files. Plotting is based around ggplot2 and is easily customizable. Advantages of nanoblots include: a robust system for designing probes to visualize isoforms including excluding reads based on the presence or absence of a specified region, an elegant solution to representing isoforms with continuous variations in length, and the ability to overlay multiple genes in the same plot using different colors. We present examples of nanoblots compared to actual northern blot data. In addition to traditional gel-like images, the NanoBlot package can also output other visualizations such as violin plots and 3'-RACE-like plots focused on 3'-ends isoforms visualization. The use of the NanoBlot package should provide a simple answer to some of the challenges of visualizing long-read RNA sequencing data.

X Demographics

X Demographics

The data shown below were collected from the profiles of 68 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 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 3 30%
Researcher 3 30%
Student > Postgraduate 1 10%
Student > Master 1 10%
Unknown 2 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 30%
Agricultural and Biological Sciences 3 30%
Unknown 4 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 35. 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 07 July 2023.
All research outputs
#1,186,767
of 25,795,662 outputs
Outputs from RNA
#41
of 3,191 outputs
Outputs of similar age
#24,600
of 410,625 outputs
Outputs of similar age from RNA
#4
of 37 outputs
Altmetric has tracked 25,795,662 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 3,191 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one has done particularly well, scoring higher than 98% 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 410,625 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 94% of its contemporaries.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.