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The Drosophila Gene Expression Tool (DGET) for expression analyses

Overview of attention for article published in BMC Bioinformatics, February 2017
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  • Good Attention Score compared to outputs of the same age and source (68th percentile)

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7 tweeters

Citations

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34 Dimensions

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59 Mendeley
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Title
The Drosophila Gene Expression Tool (DGET) for expression analyses
Published in
BMC Bioinformatics, February 2017
DOI 10.1186/s12859-017-1509-z
Pubmed ID
Authors

Yanhui Hu, Aram Comjean, Norbert Perrimon, Stephanie E. Mohr

Abstract

Next-generation sequencing technologies have greatly increased our ability to identify gene expression levels, including at specific developmental stages and in specific tissues. Gene expression data can help researchers understand the diverse functions of genes and gene networks, as well as help in the design of specific and efficient functional studies, such as by helping researchers choose the most appropriate tissue for a study of a group of genes, or conversely, by limiting a long list of gene candidates to the subset that are normally expressed at a given stage or in a given tissue. We report DGET, a Drosophila Gene Expression Tool ( www.flyrnai.org/tools/dget/web/ ), which stores and facilitates search of RNA-Seq based expression profiles available from the modENCODE consortium and other public data sets. Using DGET, researchers are able to look up gene expression profiles, filter results based on threshold expression values, and compare expression data across different developmental stages, tissues and treatments. In addition, at DGET a researcher can analyze tissue or stage-specific enrichment for an inputted list of genes (e.g., 'hits' from a screen) and search for additional genes with similar expression patterns. We performed a number of analyses to demonstrate the quality and robustness of the resource. In particular, we show that evolutionary conserved genes expressed at high or moderate levels in both fly and human tend to be expressed in similar tissues. Using DGET, we compared whole tissue profile and sub-region/cell-type specific datasets and estimated a potential source of false positives in one dataset. We also demonstrated the usefulness of DGET for synexpression studies by querying genes with expression profile similar to the mesodermal master regulator Twist. Altogether, DGET provides a flexible tool for expression data retrieval and analysis with short or long lists of Drosophila genes, which can help scientists to design stage- or tissue-specific in vivo studies and do other subsequent analyses.

Twitter Demographics

The data shown below were collected from the profiles of 7 tweeters 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 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 2%
Canada 1 2%
Unknown 57 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 29%
Student > Ph. D. Student 11 19%
Student > Bachelor 7 12%
Student > Master 6 10%
Student > Doctoral Student 4 7%
Other 7 12%
Unknown 7 12%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 22 37%
Agricultural and Biological Sciences 22 37%
Neuroscience 2 3%
Computer Science 1 2%
Psychology 1 2%
Other 3 5%
Unknown 8 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 15 May 2017.
All research outputs
#5,299,692
of 17,034,549 outputs
Outputs from BMC Bioinformatics
#2,290
of 6,064 outputs
Outputs of similar age
#124,025
of 367,183 outputs
Outputs of similar age from BMC Bioinformatics
#9
of 25 outputs
Altmetric has tracked 17,034,549 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 6,064 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has gotten more attention than average, scoring higher than 60% 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 367,183 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 65% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.