geneSurv: An interactive web-based tool for survival analysis in genomics research
Küçük Resim Yok
Tarih
2017
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Pergamon-Elsevier Science Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Survival analysis methods are often used in cancer studies. It has been shown that the combination of clinical data with genomics increases the predictive performance of survival analysis methods. But, this leads to a high-dimensional data problem. Fortunately, new methods have been developed in the last decade to overcome this problem. However, there is a strong need for easily accessible, user-friendly and interactive tool to perform survival analysis in the presence of genomics data. We developed an open-source and freely available web-based tool for survival analysis methods that can deal with high-dimensional data. This tool includes classical methods, such as Kaplan-Meier, Cox proportional hazards regression, and advanced methods, such as penalized Cox regression and Random Survival Forests. It also offers an optimal cutoff determination method based on maximizing several test statistics. The tool has a simple and interactive interface, and it can handle high dimensional data through feature selection and ensemble methods. To dichotomize gene expressions, geneSurv can identify optimal cutoff points. Users can upload their microarray, RNA-Seq, chip-Seq, proteomics, metabolomics or clinical data as a nxp dimensional data matrix, where n refers to samples and p refers to genes. This tool is available free at www.biosoft.hacettepe.edu.tr/geneSurv. All source code is available at https://github.com/selcukorkmaz/geneSurv under the GPL-3 license.
Açıklama
Anahtar Kelimeler
Survival Analysis, Genomics, Cox Regression, Kaplan-Meier, Cutoff, Feature Selection, Random Forests, Cancer, Selection, Classification, Regression, Regularization, Validation, Expression, Tests, Model
Kaynak
Computers In Biology And Medicine
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
89
