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ALSgeneScanner: a pipeline for the analysis and interpretation of DNA sequencing data of ALS patients

Iacoangeli, A; Al Khleifat, A; Sproviero, W; Shatunov, A; Jones, AR; Opie-Martin, S; Naselli, E; ... Al-Chalabi, A; + view all (2019) ALSgeneScanner: a pipeline for the analysis and interpretation of DNA sequencing data of ALS patients. Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration , 20 (3-4) pp. 207-215. 10.1080/21678421.2018.1562553. Green open access

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Abstract

Amyotrophic lateral sclerosis (ALS, MND) is a neurodegenerative disease of upper and lower motor neurons resulting in death from neuromuscular respiratory failure, typically within two years of first symptoms. Genetic factors are an important cause of ALS, with variants in more than 25 genes having strong evidence, and weaker evidence available for variants in more than 120 genes. With the increasing availability of next-generation sequencing data, non-specialists, including health care professionals and patients, are obtaining their genomic information without a corresponding ability to analyze and interpret it. Furthermore, the relevance of novel or existing variants in ALS genes is not always apparent. Here we present ALSgeneScanner, a tool that is easy to install and use, able to provide an automatic, detailed, annotated report, on a list of ALS genes from whole-genome sequencing (WGS) data in a few hours and whole exome sequence data in about 1 h on a readily available mid-range computer. This will be of value to non-specialists and aid in the interpretation of the relevance of novel and existing variants identified in DNA sequencing data.

Type: Article
Title: ALSgeneScanner: a pipeline for the analysis and interpretation of DNA sequencing data of ALS patients
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1080/21678421.2018.1562553
Publisher version: https://doi.org/10.1080/21678421.2018.1562553
Language: English
Additional information: © Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/).
Keywords: ALS, genomics, NGS, bioinformatics, genome analysis
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Clinical Epidemiology
URI: https://discovery.ucl.ac.uk/id/eprint/10072300
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