Mmrf-commpass data integration and analysis for identifying prognostic markers

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Abstract

Multiple Myeloma (MM) is the second most frequent haematological malignancy in the world although the related pathogenesis remains unclear. The study of how gene expression profiling (GEP) is correlated with patients’ survival could be important for understanding the initiation and progression of MM. In order to aid researchers in identifying new prognostic RNA biomarkers as targets for functional cell-based studies, the use of appropriate bioinformatic tools for integrative analysis is required. The main contribution of this paper is the development of a set of functionalities, extending TCGAbiolinks package, for downloading and analysing Multiple Myeloma Research Foundation (MMRF) CoMMpass study data available at the NCI’s Genomic Data Commons (GDC) Data Portal. In this context, we present further a workflow based on the use of this new functionalities that allows to i) download data; ii) perform and plot the Array Array Intensity correlation matrix; ii) correlate gene expression and Survival Analysis to obtain a Kaplan–Meier survival plot.

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Settino, M., Arbitrio, M., Scionti, F., Caracciolo, D., Di Martino, M. T., Tagliaferri, P., … Cannataro, M. (2020). Mmrf-commpass data integration and analysis for identifying prognostic markers. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12139 LNCS, pp. 564–571). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-50420-5_42

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