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Attention Score in Context
Title |
Sources of bias in measures of allele-specific expression derived from RNA-seq data aligned to a single reference genome
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Published in |
BMC Genomics, August 2013
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DOI | 10.1186/1471-2164-14-536 |
Pubmed ID | |
Authors |
Kraig R Stevenson, Joseph D Coolon, Patricia J Wittkopp |
Abstract |
RNA-seq can be used to measure allele-specific expression (ASE) by assigning sequence reads to individual alleles; however, relative ASE is systematically biased when sequence reads are aligned to a single reference genome. Aligning sequence reads to both parental genomes can eliminate this bias, but this approach is not always practical, especially for non-model organisms. To improve accuracy of ASE measured using a single reference genome, we identified properties of differentiating sites responsible for biased measures of relative ASE. |
X Demographics
The data shown below were collected from the profiles of 23 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 8 | 35% |
United Kingdom | 2 | 9% |
Spain | 1 | 4% |
Canada | 1 | 4% |
India | 1 | 4% |
Germany | 1 | 4% |
Australia | 1 | 4% |
France | 1 | 4% |
Unknown | 7 | 30% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 14 | 61% |
Members of the public | 8 | 35% |
Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 249 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 8 | 3% |
France | 3 | 1% |
Netherlands | 2 | <1% |
Germany | 1 | <1% |
Italy | 1 | <1% |
Australia | 1 | <1% |
Brazil | 1 | <1% |
Norway | 1 | <1% |
India | 1 | <1% |
Other | 3 | 1% |
Unknown | 227 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 80 | 32% |
Researcher | 69 | 28% |
Student > Master | 22 | 9% |
Student > Bachelor | 11 | 4% |
Professor | 10 | 4% |
Other | 40 | 16% |
Unknown | 17 | 7% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 146 | 59% |
Biochemistry, Genetics and Molecular Biology | 49 | 20% |
Computer Science | 11 | 4% |
Mathematics | 8 | 3% |
Medicine and Dentistry | 3 | 1% |
Other | 9 | 4% |
Unknown | 23 | 9% |
Attention Score in Context
This research output has an Altmetric Attention Score of 22. 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 08 January 2014.
All research outputs
#1,700,062
of 25,405,598 outputs
Outputs from BMC Genomics
#336
of 11,255 outputs
Outputs of similar age
#14,334
of 208,955 outputs
Outputs of similar age from BMC Genomics
#8
of 178 outputs
Altmetric has tracked 25,405,598 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,255 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 97% 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 208,955 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 93% of its contemporaries.
We're also able to compare this research output to 178 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.