Evidence map›Paper›PMID 29697367›Full record

ArticleBMC medical genomics2018

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

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

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.7field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Review
  6. Alternative RNA Splicing as a Potential Major Source of Untapped Molecular Targets in Precision Oncology and Cancer Disparities.Clinical cancer research : an official journal of the American Association for Cancer Research · 2019
    Article
  7. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Seonggyun HanDepartment of Biomedical Informatics, University of Utah, University of Utah School of Medicine, Salt Lake City, UT, 84108, USA.
Dongwook KimDepartment of Biomedical Informatics, University of Utah, University of Utah School of Medicine, Salt Lake City, UT, 84108, USA.
Youngjun KimUniversity of Utah, School of Computing, University of Utah, Salt Lake City, UT, 84108, USA.
Kanghoon ChoiDepartment of Biomedical Informatics, University of Utah, University of Utah School of Medicine, Salt Lake City, UT, 84108, USA.
Jason E MillerDepartment of Biomedical & Translational Informatics, Geisinger Health System, Danville, PA, 17822, USA.
Dokyoon KimDepartment of Biomedical & Translational Informatics, Geisinger Health System, Danville, PA, 17822, USA.
Younghee LeeDepartment of Biomedical Informatics, University of Utah, University of Utah School of Medicine, Salt Lake City, UT, 84108, USA. younghee.lee@utah.edu.
University of Utah · USGeisinger Health System · USPennsylvania State University · US

Funding

Utah Center for Clinical and Translational ScienceUL1TR002538 · NCATS · UNIVERSITY OF UTAH · PI HESS, RACHEL, MAJERSIK, JENNIFER JUHL · 2018 to 2022
$26.0M
Postdoctoral Training Program in Genomic MedicineT32HG009495 · NHGRI · UNIVERSITY OF PENNSYLVANIA · PI Katherine L. Nathanson, Bogdan Pasaniuc · 2017 to 2026
$4.2M
NCATS NIH HHS UL1 TR002538NHGRI NIH HHS T32 HG009495
6 · The paper itself

Abstract

backgroundThe 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.

resultsWe 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.

conclusionsCAS-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.

Indexed as

InternetRNA SplicingGenomicsHumansNeoplasmsPolymorphism, Single NucleotideSoftwareUrinary Bladder NeoplasmsAlternative splicingCancerGenomicsMethylationmiRNAmRNA regulationSNP

Identifiers

PMID29697367
PMCPMC5918456
OpenAlexW2801146750

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.