shinyGISPA: A web application for characterizing phenotype by gene sets using multiple omics data combinations
نویسندگان
چکیده
While many methods exist for integrating multi-omics data or defining gene sets, there is no one single tool that defines gene sets based on merging of multiple omics data sets. We present shinyGISPA, an open-source application with a user-friendly web-based interface to define genes according to their similarity in several molecular changes that are driving a disease phenotype. This tool was developed to help facilitate the usability of a previously published method, Gene Integrated Set Profile Analysis (GISPA), among researchers with limited computer-programming skills. The GISPA method allows the identification of multiple gene sets that may play a role in the characterization, clinical application, or functional relevance of a disease phenotype. The tool provides an automated workflow that is highly scalable and adaptable to applications that go beyond genomic data merging analysis. It is available at http://shinygispa.winship.emory.edu/shinyGISPA/.
منابع مشابه
INMEX—a web-based tool for integrative meta-analysis of expression data
The widespread applications of various 'omics' technologies in biomedical research together with the emergence of public data repositories have resulted in a plethora of data sets for almost any given physiological state or disease condition. Properly combining or integrating these data sets with similar basic hypotheses can help reduce study bias, increase statistical power and improve overall...
متن کاملRAMONA: a Web application for gene set analysis on multilevel omics data
SUMMARY Decreasing costs of modern high-throughput experiments allow for the simultaneous analysis of altered gene activity on various molecular levels. However, these multi-omics approaches lead to a large amount of data, which is hard to interpret for a non-bioinformatician. Here, we present the remotely accessible multilevel ontology analysis (RAMONA). It offers an easy-to-use interface for ...
متن کاملCombiROC: an interactive web tool for selecting accurate marker combinations of omics data
Diagnostic accuracy can be improved considerably by combining multiple markers, whose performance in identifying diseased subjects is usually assessed via receiver operating characteristic (ROC) curves. The selection of multimarker signatures is a complicated process that requires integration of data signatures with sophisticated statistical methods. We developed a user-friendly tool, called Co...
متن کاملOmixAnalyzer - A Web-Based System for Management and Analysis of High-Throughput Omics Data Sets
Current projects in Systems Biology often produce a multitude of different high-throughput data sets that need to be managed, processed, and analyzed in an integrated fashion. In this paper, we present the OmixAnalyzer, a web-based tool for management and analysis of heterogeneous omics data sets. It currently supports gene microarrays, miRNAs, and exon-arrays; support for mass spectrometry-bas...
متن کاملFlexible model-based clustering of mixed binary and continuous data: application to genetic regulation and cancer
Clustering is used widely in 'omics' studies and is often tackled with standard methods, e.g. hierarchical clustering. However, the increasing need for integration of multiple data sets leads to a requirement for clustering methods applicable to mixed data types, where the straightforward application of standard methods is not necessarily the best approach. A particularly common problem involve...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره 13 شماره
صفحات -
تاریخ انتشار 2018