Literature DB >> 33606250

Detecting Causal Variants in Mendelian Disorders Using Whole-Genome Sequencing.

Abdul Rezzak Hamzeh1, T Daniel Andrews1, Matt A Field2,3.   

Abstract

Increasingly affordable sequencing technologies are revolutionizing the field of genomic medicine. It is now feasible to interrogate all major classes of variation in an individual across the entire genome for less than $1000 USD. While the generation of patient sequence information using these technologies has become routine, the analysis and interpretation of this data remains the greatest obstacle to widespread clinical implementation. This chapter summarizes the steps to identify, annotate, and prioritize variant information required for clinical report generation. We discuss methods to detect each variant class and describe strategies to increase the likelihood of detecting causal variant(s) in Mendelian disease. Lastly, we describe a sample workflow for synthesizing large amount of genetic information into concise clinical reports.

Entities:  

Keywords:  Clinical reports; Copy number variation; Mendelian disease; Missense mutation; SNV; Variant annotation; Variant detection

Mesh:

Year:  2021        PMID: 33606250     DOI: 10.1007/978-1-0716-1103-6_1

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  91 in total

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  1 in total

Review 1.  Bioinformatic Challenges Detecting Genetic Variation in Precision Medicine Programs.

Authors:  Matt A Field
Journal:  Front Med (Lausanne)       Date:  2022-04-08
  1 in total

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