Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

A Framework for the RNA-Seq Based Classification and Prediction of Disease

Version 1 : Received: 6 January 2019 / Approved: 8 January 2019 / Online: 8 January 2019 (11:46:34 CET)

How to cite: Iqbal, N.; Kumar, P. A Framework for the RNA-Seq Based Classification and Prediction of Disease. Preprints 2019, 2019010068. https://doi.org/10.20944/preprints201901.0068.v1 Iqbal, N.; Kumar, P. A Framework for the RNA-Seq Based Classification and Prediction of Disease. Preprints 2019, 2019010068. https://doi.org/10.20944/preprints201901.0068.v1

Abstract

Disease classification based on biological data is an important area in bioinformatics and biomedical research. It helps the doctors and medical practitioners for the early detection of disease and support them as a computer-aided diagnostic tool for accurate diagnosis, prognosis, and treatment of disease. Earlier Microarray gene expression data have wide application for the classification of disease, but now Next-generation sequencing (NGS) has replaced the Microarray technology. From the last few years, RNA sequence (RNA-Seq) data are widely used for the transcriptomic analysis. Hence, RNA-Seq based classification of disease is in its infancy. In this article, we present a general framework for the classification of disease constructed on RNA-Seq data. This framework will guide the researchers to process RNA-Seq, extract relevant features and apply the appropriate classifier to classify any kind of disease.

Keywords

disease classification; read mapping; feature selection; machine learning

Subject

Biology and Life Sciences, Biochemistry and Molecular Biology

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