Journal of Biology and Life Science ISSN 2157-6076 2017, Vol. 8, No. 2 57 An Overview of RNA-seq Data Analysis Tahsin Ferdous Department of Statistics, Shahjalal University of Science and Technology, Bangladesh. E-mail: tahsinferdous29@gmail.com Mohammad Ohid Ullah (Corresponding author) Department of Statistics, Shahjalal University of Science and Technology, Bangladesh. E-mail: ohid-sta@sust.edu Received: May 22, 2017 Accepted: June 8, 2017 Published: August 3, 2017 doi:10.5296/jbls.v8i2.11255 URL: https://doi.org/10.5296/jbls.v8i2.11255 Abstract Latest breakthrough in high-throughput DNA sequencing have been launched different arenas for transcriptome analyses, jointly named RNA-seq (RNA-sequencing). It exposes the existence and amount of RNA in a biotic sample at a specific time by utilizing next generation sequencing (NGS). In this review, we aimed to explore the several methods which are applied in analyzing RNA-seq data. We also discussed its importance over microarray data. As establishment of several methods have already taken place to analyze RNA-seq data, therefore, further analysis is very essential to select the best one to avoid false positive outcomes. Keywords: RNA-seq, transcriptome, Methods, Models, NGS 1. Introduction 1.1 Gene Expression The information contained within a gene turns into an effective product by gene expression. Genes can be expressed as RNA and translated into protein; expression arises one at the transcription level, in which RNA is produced from DNA, and one at the protein level, where protein is created from mRNA Several different steps are included through which DNA is transcribed into RNA and this in turn is modified into a protein or in some cases an RNA