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Computational Biology of Non-Coding RNA pp 55–76Cite as

Methods for Annotation and Validation of Circular RNAs from RNAseq Data

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 1912))

Abstract

Circular RNAs are an emerging class of transcript isoforms created by unique back splicing of exons to form a closed covalent circular structure. While initially considered as product of aberrant splicing, recent evidence suggests unique functions and conservation across evolution. While circular RNAs could be largely attributed to have little or no potential to encode for proteins, recent evidence points to at least a small subset of circular RNAs which encode for peptides. Circular RNAs are also increasingly shown to be biomarkers for a number of diseases including neurological disorders and cancer. The advent of deep sequencing has enabled large-scale identification of circular RNAs in human and other genomes. A number of computational approaches have come up in recent years to query circular RNAs on a genome-wide scale from RNA-seq data. In this chapter, we describe the application and methodology of identifying circular RNAs using three popular computational tools: FindCirc, Segemehl, and CIRI along with approaches for experimental validation of the unique splice junctions.

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Author information

Authors and Affiliations

  1. G.N. Ramachandran Knowledge Center for Bioinformatics, CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India

    Disha Sharma, Judith Hariprakash & Vinod Scaria

  2. Academy of Scientific and Innovative Research (AcSIR), CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India

    Disha Sharma, Paras Sehgal, Sridhar Sivasubbu & Vinod Scaria

  3. Genomics and Molecular Medicine, CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India

    Paras Sehgal & Sridhar Sivasubbu

Authors
  1. Disha Sharma
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  2. Paras Sehgal
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  3. Judith Hariprakash
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  4. Sridhar Sivasubbu
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  5. Vinod Scaria
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Corresponding author

Correspondence to Vinod Scaria .

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Editors and Affiliations

  1. Department of Dermatology, Erlangen University Hospital, Erlangen, Germany

    Xin Lai

  2. Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany

    Shailendra K. Gupta

  3. Department of Dermatology, Erlangen University Hospital, Erlangen, Germany

    Julio Vera

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Sharma, D., Sehgal, P., Hariprakash, J., Sivasubbu, S., Scaria, V. (2019). Methods for Annotation and Validation of Circular RNAs from RNAseq Data. In: Lai, X., Gupta, S., Vera, J. (eds) Computational Biology of Non-Coding RNA. Methods in Molecular Biology, vol 1912. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8982-9_3

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  • DOI: https://doi.org/10.1007/978-1-4939-8982-9_3

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-8981-2

  • Online ISBN: 978-1-4939-8982-9

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