Abstract
Recent advances in next-generation sequencing technology allow high-throughput RNA sequencing (RNA-Seq) to be widely applied in transcriptomic studies. For model organisms with a reference genome, the first step in analysis of RNA-Seq data involves mapping of short-read sequences to the reference genome. Reference-guided transcriptome assembly is an optional step, which is recommended if the aim is to identify novel transcripts. Following read mapping, the primary interest of biologists in many RNA-Seq studies is the investigation of differential expression between experimental groups. In this review, we discuss recent developments in RNA-Seq data analysis applied to model organisms, including methods and algorithms for direct mapping, reference-guided transcriptome assembly and differential expression analysis, and provide insights for the future direction of RNA-Seq.
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This article is dedicated to the Special Collection of Recent Advances in Next-Generation Bioinformatics (Ed. Xuegong Zhang).
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Zhao, QY., Gratten, J., Restuadi, R. et al. Mapping and differential expression analysis from short-read RNA-Seq data in model organisms. Quant Biol 4, 22–35 (2016). https://doi.org/10.1007/s40484-016-0060-7
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DOI: https://doi.org/10.1007/s40484-016-0060-7