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TCGA2BED: extracting, extending, integrating, and querying The Cancer Genome Atlas

Overview of attention for article published in BMC Bioinformatics, January 2017
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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 (89th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

blogs
1 blog
twitter
13 X users
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

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34 Dimensions

Readers on

mendeley
69 Mendeley
Title
TCGA2BED: extracting, extending, integrating, and querying The Cancer Genome Atlas
Published in
BMC Bioinformatics, January 2017
DOI 10.1186/s12859-016-1419-5
Pubmed ID
Authors

Fabio Cumbo, Giulia Fiscon, Stefano Ceri, Marco Masseroli, Emanuel Weitschek

Abstract

Data extraction and integration methods are becoming essential to effectively access and take advantage of the huge amounts of heterogeneous genomics and clinical data increasingly available. In this work, we focus on The Cancer Genome Atlas, a comprehensive archive of tumoral data containing the results of high-throughout experiments, mainly Next Generation Sequencing, for more than 30 cancer types. We propose TCGA2BED a software tool to search and retrieve TCGA data, and convert them in the structured BED format for their seamless use and integration. Additionally, it supports the conversion in CSV, GTF, JSON, and XML standard formats. Furthermore, TCGA2BED extends TCGA data with information extracted from other genomic databases (i.e., NCBI Entrez Gene, HGNC, UCSC, and miRBase). We also provide and maintain an automatically updated data repository with publicly available Copy Number Variation, DNA-methylation, DNA-seq, miRNA-seq, and RNA-seq (V1,V2) experimental data of TCGA converted into the BED format, and their associated clinical and biospecimen meta data in attribute-value text format. The availability of the valuable TCGA data in BED format reduces the time spent in taking advantage of them: it is possible to efficiently and effectively deal with huge amounts of cancer genomic data integratively, and to search, retrieve and extend them with additional information. The BED format facilitates the investigators allowing several knowledge discovery analyses on all tumor types in TCGA with the final aim of understanding pathological mechanisms and aiding cancer treatments.

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 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 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 1%
China 1 1%
Italy 1 1%
Unknown 66 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 26%
Student > Ph. D. Student 13 19%
Student > Master 9 13%
Student > Postgraduate 4 6%
Other 4 6%
Other 8 12%
Unknown 13 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 19 28%
Agricultural and Biological Sciences 17 25%
Computer Science 10 14%
Medicine and Dentistry 6 9%
Nursing and Health Professions 1 1%
Other 4 6%
Unknown 12 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 31 August 2017.
All research outputs
#2,081,978
of 22,931,367 outputs
Outputs from BMC Bioinformatics
#540
of 7,306 outputs
Outputs of similar age
#45,260
of 421,214 outputs
Outputs of similar age from BMC Bioinformatics
#10
of 138 outputs
Altmetric has tracked 22,931,367 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,306 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 92% 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 421,214 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 89% of its contemporaries.
We're also able to compare this research output to 138 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 92% of its contemporaries.