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Proteomic Validation of Transcript Isoforms, Including Those Assembled from RNA-Seq Data

Overview of attention for article published in Journal of Proteome Research, May 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

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1 blog
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66 Mendeley
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Title
Proteomic Validation of Transcript Isoforms, Including Those Assembled from RNA-Seq Data
Published in
Journal of Proteome Research, May 2015
DOI 10.1021/pr5011394
Pubmed ID
Authors

Aidan P. Tay, Chi Nam Ignatius Pang, Natalie A. Twine, Gene Hart-Smith, Linda Harkness, Moustapha Kassem, Marc R. Wilkins

Abstract

Human proteome analysis now requires an understanding of protein isoforms. We recently published the PG Nexus pipeline, which facilitates high confidence validation of exons and splice junctions by integrating genomics and proteomics data. Here we comprehensively explore how RNA-seq transcriptomics data, and proteomic analysis of the same sample, can identify protein isoforms. RNA-seq data from human mesenchymal (hMSC) stem cells were analysed with our new TranscriptCoder tool to generate a database of protein isoform sequences. MS/MS data from matching hMSC samples were then matched against the TranscriptCoder-derived database, along with Ensembl and the neXtProt database. Querying the TranscriptCoder-derived or Ensembl database could unambiguously identify ~450 protein isoforms, with isoform-specific proteotypic peptides, including candidate hMSC-specific isoforms for the genes DPYSL2 and FXR1. Where isoform-specific peptides did not exist, groups of non-isoform-specific proteotypic peptides could specifically identify many isoforms. In both the above cases, isoforms will be detectable with targeted MS/MS assays. Unfortunately, our analysis also revealed that some isoforms will be difficult to identify unambiguously as they do not have peptides that are sufficiently distinguishing. We co-visualise mRNA isoforms and peptides in a genome browser to illustrate the above situations. Mass spectrometry data is available via ProteomeXchange (PXD001449).

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 5%
Czechia 1 2%
Australia 1 2%
Denmark 1 2%
Slovenia 1 2%
Unknown 59 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 27%
Researcher 13 20%
Other 5 8%
Student > Master 4 6%
Professor 4 6%
Other 13 20%
Unknown 9 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 19 29%
Agricultural and Biological Sciences 16 24%
Chemistry 6 9%
Unspecified 3 5%
Computer Science 3 5%
Other 7 11%
Unknown 12 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 10 June 2016.
All research outputs
#2,296,424
of 23,577,761 outputs
Outputs from Journal of Proteome Research
#488
of 6,148 outputs
Outputs of similar age
#30,364
of 268,115 outputs
Outputs of similar age from Journal of Proteome Research
#2
of 89 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,148 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has done particularly well, scoring higher than 92% 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 268,115 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 88% of its contemporaries.
We're also able to compare this research output to 89 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 97% of its contemporaries.