CANCERTOOL: A Visualization and Representation Interface to Exploit Cancer Datasets
Language English Country United States Media print-electronic
Document type Journal Article, Research Support, Non-U.S. Gov't
PubMed
30232219
DOI
10.1158/0008-5472.can-18-1669
PII: 0008-5472.CAN-18-1669
Knihovny.cz E-resources
- MeSH
- Algorithms MeSH
- Databases, Factual MeSH
- Databases, Genetic MeSH
- Genomics MeSH
- Internet MeSH
- Medical Oncology MeSH
- Humans MeSH
- Neoplasms genetics MeSH
- Computer Graphics MeSH
- Proteomics MeSH
- Workflow MeSH
- Software MeSH
- Transcriptome MeSH
- User-Computer Interface MeSH
- Computational Biology methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
With the advent of OMICs technologies, both individual research groups and consortia have spear-headed the characterization of human samples of multiple pathophysiologic origins, resulting in thousands of archived genomes and transcriptomes. Although a variety of web tools are now available to extract information from OMICs data, their utility has been limited by the capacity of nonbioinformatician researchers to exploit the information. To address this problem, we have developed CANCERTOOL, a web-based interface that aims to overcome the major limitations of public transcriptomics dataset analysis for highly prevalent types of cancer (breast, prostate, lung, and colorectal). CANCERTOOL provides rapid and comprehensive visualization of gene expression data for the gene(s) of interest in well-annotated cancer datasets. This visualization is accompanied by generation of reports customized to the interest of the researcher (e.g., editable figures, detailed statistical analyses, and access to raw data for reanalysis). It also carries out gene-to-gene correlations in multiple datasets at the same time or using preset patient groups. Finally, this new tool solves the time-consuming task of performing functional enrichment analysis with gene sets of interest using up to 11 different databases at the same time. Collectively, CANCERTOOL represents a simple and freely accessible interface to interrogate well-annotated datasets and obtain publishable representations that can contribute to refinement and guidance of cancer-related investigations at all levels of hypotheses and design.Significance: In order to facilitate access of research groups without bioinformatics support to public transcriptomics data, we have developed a free online tool with an easy-to-use interface that allows researchers to obtain quality information in a readily publishable format. Cancer Res; 78(21); 6320-8. ©2018 AACR.
Biochemistry and Molecular Biology Department University of the Basque Country Bilbao Spain
Bioinformatics Unit Center for Applied Medical Research University of Navarra Pamplona Spain
Center for Applied Medical Research Program of Solid Tumors University of Navarra Pamplona Spain
Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas Madrid Spain
CIC bioGUNE Bizkaia Technology Park Bizkaia Spain
Departamento de Bioquímica y Biología Molecular Universidad de Oviedo Oviedo Spain
IdiSNA Navarra Institute for Health Research Pamplona Spain
Ikerbasque Basque Foundation for Science Bilbao Spain
Institució Catalana de Recerca i Estudis Avançats Barcelona Spain
University Hospital Motol Prague Czech Republic
University of Navarra Department of Histology and Pathology Pamplona Spain
University of Navarra Tecnun School of Engineering San Sebastián Spain
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