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CGDV: a webtool for circular visualization of genomics and transcriptomics data

Overview of attention for article published in BMC Genomics, October 2017
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Title
CGDV: a webtool for circular visualization of genomics and transcriptomics data
Published in
BMC Genomics, October 2017
DOI 10.1186/s12864-017-4169-5
Pubmed ID
Authors

Vineet Jha, Gulzar Singh, Shiva Kumar, Amol Sonawane, Abhay Jere, Krishanpal Anamika

Abstract

Interpretation of large-scale data is very challenging and currently there is scarcity of web tools which support automated visualization of a variety of high throughput genomics and transcriptomics data and for a wide variety of model organisms along with user defined karyotypes. Circular plot provides holistic visualization of high throughput large scale data but it is very complex and challenging to generate as most of the available tools need informatics expertise to install and run them. We have developed CGDV (Circos for Genomics and Transcriptomics Data Visualization), a webtool based on Circos, for seamless and automated visualization of a variety of large scale genomics and transcriptomics data. CGDV takes output of analyzed genomics or transcriptomics data of different formats, such as vcf, bed, xls, tab limited matrix text file, CNVnator raw output and Gene fusion raw output, to plot circular view of the sample data. CGDV take cares of generating intermediate files required for circos. CGDV is freely available at https://cgdv-upload.persistent.co.in/cgdv/ . The circular plot for each data type is tailored to gain best biological insights into the data. The inter-relationship between data points, homologous sequences, genes involved in fusion events, differential expression pattern, sequencing depth, types and size of variations and enrichment of DNA binding proteins can be seen using CGDV. CGDV thus helps biologists and bioinformaticians to visualize a variety of genomics and transcriptomics data seamlessly.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 56 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 13 23%
Researcher 12 21%
Student > Ph. D. Student 10 18%
Student > Bachelor 4 7%
Other 3 5%
Other 7 13%
Unknown 7 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 18 32%
Agricultural and Biological Sciences 18 32%
Computer Science 3 5%
Medicine and Dentistry 2 4%
Engineering 2 4%
Other 4 7%
Unknown 9 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 30 October 2017.
All research outputs
#18,574,814
of 23,006,268 outputs
Outputs from BMC Genomics
#8,225
of 10,693 outputs
Outputs of similar age
#250,949
of 327,740 outputs
Outputs of similar age from BMC Genomics
#163
of 210 outputs
Altmetric has tracked 23,006,268 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,693 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
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We're also able to compare this research output to 210 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.