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CAS-viewer: web-based tool for splicing-guided integrative analysis of multi-omics cancer data

Overview of attention for article published in BMC Medical Genomics, April 2018
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Mentioned by

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3 tweeters

Citations

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10 Dimensions

Readers on

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36 Mendeley
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Title
CAS-viewer: web-based tool for splicing-guided integrative analysis of multi-omics cancer data
Published in
BMC Medical Genomics, April 2018
DOI 10.1186/s12920-018-0348-8
Pubmed ID
Authors

Seonggyun Han, Dongwook Kim, Youngjun Kim, Kanghoon Choi, Jason E. Miller, Dokyoon Kim, Younghee Lee

Abstract

The Cancer Genome Atlas (TCGA) project is a public resource that provides transcriptomic, DNA sequence, methylation, and clinical data for 33 cancer types. Transforming the large size and high complexity of TCGA cancer genome data into integrated knowledge can be useful to promote cancer research. Alternative splicing (AS) is a key regulatory mechanism of genes in human cancer development and in the interaction with epigenetic factors. Therefore, AS-guided integration of existing TCGA data sets will make it easier to gain insight into the genetic architecture of cancer risk and related outcomes. There are already existing tools analyzing and visualizing alternative mRNA splicing patterns for large-scale RNA-seq experiments. However, these existing web-based tools are limited to the analysis of individual TCGA data sets at a time, such as only transcriptomic information. We implemented CAS-viewer (integrative analysis of Cancer genome data based on Alternative Splicing), a web-based tool leveraging multi-cancer omics data from TCGA. It illustrates alternative mRNA splicing patterns along with methylation, miRNAs, and SNPs, and then provides an analysis tool to link differential transcript expression ratio to methylation, miRNA, and splicing regulatory elements for 33 cancer types. Moreover, one can analyze AS patterns with clinical data to identify potential transcripts associated with different survival outcome for each cancer. CAS-viewer is a web-based application for transcript isoform-driven integration of multi-omics data in multiple cancer types and will aid in the visualization and possible discovery of biomarkers for cancer by integrating multi-omics data from TCGA.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 25%
Student > Ph. D. Student 7 19%
Other 3 8%
Professor > Associate Professor 2 6%
Student > Master 2 6%
Other 3 8%
Unknown 10 28%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 22%
Agricultural and Biological Sciences 5 14%
Medicine and Dentistry 2 6%
Veterinary Science and Veterinary Medicine 1 3%
Computer Science 1 3%
Other 1 3%
Unknown 18 50%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 27 April 2018.
All research outputs
#10,249,884
of 16,638,522 outputs
Outputs from BMC Medical Genomics
#476
of 880 outputs
Outputs of similar age
#159,278
of 282,036 outputs
Outputs of similar age from BMC Medical Genomics
#5
of 8 outputs
Altmetric has tracked 16,638,522 research outputs across all sources so far. This one is in the 36th percentile – i.e., 36% of other outputs scored the same or lower than it.
So far Altmetric has tracked 880 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 40th percentile – i.e., 40% of its peers scored the same or lower than it.
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 282,036 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.