Resumen
| Idioma original | English |
|---|---|
| Publicación | PLoS One |
| DOI | |
| Estado | Published - 16 sep 2013 |
| Publicado de forma externa | Sí |
Huella dactilar
All Science Journal Classification (ASJC) codes
- Biochemistry, Genetics and Molecular Biology(all)
- Agricultural and Biological Sciences(all)
Citar esto
}
SurvExpress: An Online Biomarker Validation Tool and Database for Cancer Gene Expression Data Using Survival Analysis. / Aguirre-Gamboa, Raul; Gomez-Rueda, Hugo; Martínez-Ledesma, Emmanuel; Martínez-Torteya, Antonio; Chacolla-Huaringa, Rafael; Rodriguez-Barrientos, Alberto; Tamez-Peña, José G.; Treviño, Victor.
En: PLoS One, 16.09.2013.Resultado de la investigación
TY - JOUR
T1 - SurvExpress: An Online Biomarker Validation Tool and Database for Cancer Gene Expression Data Using Survival Analysis
AU - Aguirre-Gamboa, Raul
AU - Gomez-Rueda, Hugo
AU - Martínez-Ledesma, Emmanuel
AU - Martínez-Torteya, Antonio
AU - Chacolla-Huaringa, Rafael
AU - Rodriguez-Barrientos, Alberto
AU - Tamez-Peña, José G.
AU - Treviño, Victor
PY - 2013/9/16
Y1 - 2013/9/16
N2 - Validation of multi-gene biomarkers for clinical outcomes is one of the most important issues for cancer prognosis. An important source of information for virtual validation is the high number of available cancer datasets. Nevertheless, assessing the prognostic performance of a gene expression signature along datasets is a difficult task for Biologists and Physicians and also time-consuming for Statisticians and Bioinformaticians. Therefore, to facilitate performance comparisons and validations of survival biomarkers for cancer outcomes, we developed SurvExpress, a cancer-wide gene expression database with clinical outcomes and a web-based tool that provides survival analysis and risk assessment of cancer datasets. The main input of SurvExpress is only the biomarker gene list. We generated a cancer database collecting more than 20,000 samples and 130 datasets with censored clinical information covering tumors over 20 tissues. We implemented a web interface to perform biomarker validation and comparisons in this database, where a multivariate survival analysis can be accomplished in about one minute. We show the utility and simplicity of SurvExpress in two biomarker applications for breast and lung cancer. Compared to other tools, SurvExpress is the largest, most versatile, and quickest free tool available. SurvExpress web can be accessed in http://bioinformatica.mty.itesm.mx/SurvExpress (a tutorial is included). The website was implemented in JSP, JavaScript, MySQL, and R. © 2013 Aguirre-Gamboa et al.
AB - Validation of multi-gene biomarkers for clinical outcomes is one of the most important issues for cancer prognosis. An important source of information for virtual validation is the high number of available cancer datasets. Nevertheless, assessing the prognostic performance of a gene expression signature along datasets is a difficult task for Biologists and Physicians and also time-consuming for Statisticians and Bioinformaticians. Therefore, to facilitate performance comparisons and validations of survival biomarkers for cancer outcomes, we developed SurvExpress, a cancer-wide gene expression database with clinical outcomes and a web-based tool that provides survival analysis and risk assessment of cancer datasets. The main input of SurvExpress is only the biomarker gene list. We generated a cancer database collecting more than 20,000 samples and 130 datasets with censored clinical information covering tumors over 20 tissues. We implemented a web interface to perform biomarker validation and comparisons in this database, where a multivariate survival analysis can be accomplished in about one minute. We show the utility and simplicity of SurvExpress in two biomarker applications for breast and lung cancer. Compared to other tools, SurvExpress is the largest, most versatile, and quickest free tool available. SurvExpress web can be accessed in http://bioinformatica.mty.itesm.mx/SurvExpress (a tutorial is included). The website was implemented in JSP, JavaScript, MySQL, and R. © 2013 Aguirre-Gamboa et al.
U2 - 10.1371/journal.pone.0074250
DO - 10.1371/journal.pone.0074250
M3 - Article
JO - PLoS One
JF - PLoS One
SN - 1932-6203
ER -