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Combination of novel and public RNA-seq datasets to generate an mRNA expression atlas for the domestic chicken

Overview of attention for article published in BMC Genomics, August 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

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Title
Combination of novel and public RNA-seq datasets to generate an mRNA expression atlas for the domestic chicken
Published in
BMC Genomics, August 2018
DOI 10.1186/s12864-018-4972-7
Pubmed ID
Authors

Stephen J. Bush, Lucy Freem, Amanda J. MacCallum, Jenny O’Dell, Chunlei Wu, Cyrus Afrasiabi, Androniki Psifidi, Mark P. Stevens, Jacqueline Smith, Kim M. Summers, David A. Hume

Abstract

The domestic chicken (Gallus gallus) is widely used as a model in developmental biology and is also an important livestock species. We describe a novel approach to data integration to generate an mRNA expression atlas for the chicken spanning major tissue types and developmental stages, using a diverse range of publicly-archived RNA-seq datasets and new data derived from immune cells and tissues. Randomly down-sampling RNA-seq datasets to a common depth and quantifying expression against a reference transcriptome using the mRNA quantitation tool Kallisto ensured that disparate datasets explored comparable transcriptomic space. The network analysis tool Graphia was used to extract clusters of co-expressed genes from the resulting expression atlas, many of which were tissue or cell-type restricted, contained transcription factors that have previously been implicated in their regulation, or were otherwise associated with biological processes, such as the cell cycle. The atlas provides a resource for the functional annotation of genes that currently have only a locus ID. We cross-referenced the RNA-seq atlas to a publicly available embryonic Cap Analysis of Gene Expression (CAGE) dataset to infer the developmental time course of organ systems, and to identify a signature of the expansion of tissue macrophage populations during development. Expression profiles obtained from public RNA-seq datasets - despite being generated by different laboratories using different methodologies - can be made comparable to each other. This meta-analytic approach to RNA-seq can be extended with new datasets from novel tissues, and is applicable to any species.

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The data shown below were collected from the profiles of 12 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 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 20%
Researcher 6 15%
Student > Bachelor 5 12%
Student > Master 4 10%
Student > Postgraduate 2 5%
Other 5 12%
Unknown 11 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 29%
Biochemistry, Genetics and Molecular Biology 10 24%
Computer Science 2 5%
Medicine and Dentistry 2 5%
Veterinary Science and Veterinary Medicine 1 2%
Other 4 10%
Unknown 10 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 11 June 2019.
All research outputs
#5,738,061
of 23,099,576 outputs
Outputs from BMC Genomics
#2,347
of 10,706 outputs
Outputs of similar age
#98,155
of 330,798 outputs
Outputs of similar age from BMC Genomics
#40
of 176 outputs
Altmetric has tracked 23,099,576 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,706 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 77% 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 330,798 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 176 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.