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Identification of Genetic Variants and de novo Mutations Based on NGS

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Next Generation Sequencing and Data Analysis

Part of the book series: Learning Materials in Biosciences ((LMB))

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What you will learn

In this chapter, we will discuss an overview of the bioinformatic process for the identification of genetic variants and de novo mutations in data recovered from NGS applications. We will pinpoint critical steps, describe the theoretical basis of different variant calling algorithms, describe data formats, and review the different filtering criteria that can be undertaken to obtain a set of high-confidence mutations. We will also go over crucial issues to take into account when analyzing NGS data, such as tissue source or the choice of sequencing machine. We also discuss different methodologies for analyzing these variants depending on study context, considering population-wide and family-focused analyses. Finally, we also do an overview of available software for variant filtering and genetic data visualization.

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Acknowledgements

We thank Dr. Stefan Fischer (Biochemist at the Faculty of Applied Informatics, Deggendorf Institute of Technology, Germany), and Dr. Petr Danecek (Wellcome Sanger Institute, United Kingdom) for reviewing this chapter and suggesting extremely relevant enhancements to the original manuscript.

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Authors and Affiliations

  1. Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Campus Juriquilla, Santiago de Querétaro, México

    Patricia Basurto-Lozada, Carolina Castañeda-Garcia, Raúl Ossio & Carla Daniela Robles-Espinoza

  2. Experimental Cancer Genetics, Wellcome Sanger Institute, Cambridge, UK

    Carla Daniela Robles-Espinoza

Authors
  1. Patricia Basurto-Lozada
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  2. Carolina Castañeda-Garcia
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  3. Raúl Ossio
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  4. Carla Daniela Robles-Espinoza
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Corresponding author

Correspondence to Carla Daniela Robles-Espinoza .

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Editors and Affiliations

  1. Faculty of Applied Informatics, Deggendorf Institute of Technology, Deggendorf, Germany

    Melanie Kappelmann-Fenzl

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Basurto-Lozada, P., Castañeda-Garcia, C., Ossio, R., Robles-Espinoza, C.D. (2021). Identification of Genetic Variants and de novo Mutations Based on NGS. In: Kappelmann-Fenzl, M. (eds) Next Generation Sequencing and Data Analysis. Learning Materials in Biosciences. Springer, Cham. https://doi.org/10.1007/978-3-030-62490-3_10

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