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A Guide to RNAseq Data Analysis Using Bioinformatics Approaches

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Abstract

The emergence of Next Generation Sequencing (NGS), such as DNA, RNA and other small RNA sequencing technologies, gave rise to a huge amount of raw data on a massive scale. To analyse that data and to obtain the biological interpretation as a challenging act, advancements in computational biology and bioinformatics applications emerged as the need of the hour. RNAseq accounts for exploration of comprehensive expression profile of genes and quantifies the presence of RNA content in the biological sample. In addition to this, RNAseq also provides information for alternative splice variants, novel gene identification, differentially expressing genes, etc. The workflow for RNAseq data analysis requires quality check of the data, mapping onto a reference genome/transcriptome, read quantification, differential expression analysis and functional annotation. Various tools and softwares with different algorithms have been developed to provide biological understanding of the data and to meet the demands of the analyst. An overview of the tools and softwares has been provided in the chapter that can be exploited to analyse the data for different investigations. Also, a glimpse of other RNAseq techniques such as single cell RNAseq and small RNA sequencing has been discussed as an introduction to newer forms of RNA sequencing.

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Authors and Affiliations

  1. Department of Zoology, Biomedical Technology and Human Genetics, University School of Sciences, Gujarat University, Ahmedabad, Gujarat, India

    Preeti Sharma & Ramtej J. Verma

  2. PanGenomics International Pvt Ltd, Sterling Accuris Diagnostics, Ahmedabad, Gujarat, India

    Preeti Sharma

  3. Genexplore Diagnostics and Research Centre, Ahmedabad, Gujarat, India

    B. Sharan Sharma

  4. Rivaara Labs Pvt Ltd, KD Hospital, Ahmedabad, Gujarat, India

    B. Sharan Sharma

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  1. Preeti Sharma
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  2. B. Sharan Sharma
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  1. Department of Biosciences, Indrashil University, Mehsana, Gujarat, India

    Vijai Singh

  2. Biotechnology, Rama University, Kanpur, Uttar Pradesh, India

    Ajay Kumar

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Sharma, P., Sharma, B.S., Verma, R.J. (2021). A Guide to RNAseq Data Analysis Using Bioinformatics Approaches. In: Singh, V., Kumar, A. (eds) Advances in Bioinformatics. Springer, Singapore. https://doi.org/10.1007/978-981-33-6191-1_12

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