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cDNA Hybrid Capture Improves Transcriptome Analysis on Low-Input and Archived Samples

Overview of attention for article published in The Journal of Molecular Diagnostics, July 2014
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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 (84th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

blogs
1 blog
twitter
1 tweeter

Citations

dimensions_citation
23 Dimensions

Readers on

mendeley
38 Mendeley
citeulike
2 CiteULike
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Title
cDNA Hybrid Capture Improves Transcriptome Analysis on Low-Input and Archived Samples
Published in
The Journal of Molecular Diagnostics, July 2014
DOI 10.1016/j.jmoldx.2014.03.004
Pubmed ID
Authors

Christopher R. Cabanski, Vincent Magrini, Malachi Griffith, Obi L. Griffith, Sean McGrath, Jin Zhang, Jason Walker, Amy Ly, Ryan Demeter, Robert S. Fulton, Winnie W. Pong, David H. Gutmann, Ramaswamy Govindan, Elaine R. Mardis, Christopher A. Maher

Abstract

The use of massively parallel sequencing for studying RNA expression has greatly enhanced our understanding of the transcriptome through the myriad ways these data can be characterized. In particular, clinical samples provide important insights about RNA expression in health and disease, yet these studies can be complicated by RNA degradation that results from the use of formalin as a clinical preservative and by the limited amounts of RNA often available from these precious samples. In this study we describe the combined use of RNA sequencing with an exome capture selection step to enhance the yield of on-exon sequencing read data when compared with RNA sequencing alone. In particular, the exome capture step preserves the dynamic range of expression, permitting differential comparisons and validation of expressed mutations from limited and FFPE preserved samples, while reducing the data generation requirement. We conclude that cDNA hybrid capture has the potential to significantly improve transcriptome analysis from low-yield FFPE material.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 5%
South Africa 1 3%
United States 1 3%
Unknown 34 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 42%
Student > Ph. D. Student 9 24%
Student > Bachelor 3 8%
Student > Master 2 5%
Other 2 5%
Other 6 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 45%
Biochemistry, Genetics and Molecular Biology 11 29%
Medicine and Dentistry 4 11%
Immunology and Microbiology 3 8%
Unspecified 2 5%
Other 1 3%

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 09 October 2018.
All research outputs
#1,736,894
of 11,993,883 outputs
Outputs from The Journal of Molecular Diagnostics
#141
of 746 outputs
Outputs of similar age
#31,540
of 202,713 outputs
Outputs of similar age from The Journal of Molecular Diagnostics
#3
of 10 outputs
Altmetric has tracked 11,993,883 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 746 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.3. This one has done well, scoring higher than 80% 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 202,713 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 84% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 7 of them.