Challenging popular tools for the annotation of genetic variations with a real case, pathogenic mutations of lysosomal alpha-galactosidase
Abstract Background Severity gradation of missense mutations is a big challenge for exome annotation. Predictors of deleteriousness that are most frequently used to filter variants found by next generation sequencing, produce qualitative predictions, but also numerical scores. It has never been test...
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doaj-cf7aa86ffc894da5afe73be8e7f0bf202020-11-25T02:17:59ZengBMCBMC Bioinformatics1471-21052018-11-0119S15394610.1186/s12859-018-2416-7Challenging popular tools for the annotation of genetic variations with a real case, pathogenic mutations of lysosomal alpha-galactosidaseChiara Cimmaruta0Valentina Citro1Giuseppina Andreotti2Ludovica Liguori3Maria Vittoria Cubellis4Bruno Hay Mele5Dipartimento di Biologia, Complesso di Monte Sant’Angelo, Università Federico IIDipartimento di Biologia, Complesso di Monte Sant’Angelo, Università Federico IIIstituto di Chimica Biomolecolare, Consiglio Nazionale delle RicercheDipartimento di Scienze e Tecnologie Ambientali, Biologiche e Farmaceutiche, Università della Campania “Luigi Vanvitelli”Dipartimento di Biologia, Complesso di Monte Sant’Angelo, Università Federico IIDipartimento di Biologia, Complesso di Monte Sant’Angelo, Università Federico IIAbstract Background Severity gradation of missense mutations is a big challenge for exome annotation. Predictors of deleteriousness that are most frequently used to filter variants found by next generation sequencing, produce qualitative predictions, but also numerical scores. It has never been tested if these scores correlate with disease severity. Results wANNOVAR, a popular tool that can generate several different types of deleteriousness-prediction scores, was tested on Fabry disease. This pathology, which is caused by a deficit of lysosomal alpha-galactosidase, has a very large genotypic and phenotypic spectrum and offers the possibility of associating a quantitative measure of the damage caused by mutations to the functioning of the enzyme in the cells. Some predictors, and in particular VEST3 and PolyPhen2 provide scores that correlate with the severity of lysosomal alpha-galactosidase mutations in a statistically significant way. Conclusions Sorting disease mutations by severity is possible and offers advantages over binary classification. Dataset for testing and training in silico predictors can be obtained by transient transfection and evaluation of residual activity of mutants in cell extracts. This approach consents to quantitative data for severe, mild and non pathological variants.http://link.springer.com/article/10.1186/s12859-018-2416-7Rare diseaseClinical informaticsVariant analysisBioinformaticsFabry disease |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Chiara Cimmaruta Valentina Citro Giuseppina Andreotti Ludovica Liguori Maria Vittoria Cubellis Bruno Hay Mele |
spellingShingle |
Chiara Cimmaruta Valentina Citro Giuseppina Andreotti Ludovica Liguori Maria Vittoria Cubellis Bruno Hay Mele Challenging popular tools for the annotation of genetic variations with a real case, pathogenic mutations of lysosomal alpha-galactosidase BMC Bioinformatics Rare disease Clinical informatics Variant analysis Bioinformatics Fabry disease |
author_facet |
Chiara Cimmaruta Valentina Citro Giuseppina Andreotti Ludovica Liguori Maria Vittoria Cubellis Bruno Hay Mele |
author_sort |
Chiara Cimmaruta |
title |
Challenging popular tools for the annotation of genetic variations with a real case, pathogenic mutations of lysosomal alpha-galactosidase |
title_short |
Challenging popular tools for the annotation of genetic variations with a real case, pathogenic mutations of lysosomal alpha-galactosidase |
title_full |
Challenging popular tools for the annotation of genetic variations with a real case, pathogenic mutations of lysosomal alpha-galactosidase |
title_fullStr |
Challenging popular tools for the annotation of genetic variations with a real case, pathogenic mutations of lysosomal alpha-galactosidase |
title_full_unstemmed |
Challenging popular tools for the annotation of genetic variations with a real case, pathogenic mutations of lysosomal alpha-galactosidase |
title_sort |
challenging popular tools for the annotation of genetic variations with a real case, pathogenic mutations of lysosomal alpha-galactosidase |
publisher |
BMC |
series |
BMC Bioinformatics |
issn |
1471-2105 |
publishDate |
2018-11-01 |
description |
Abstract Background Severity gradation of missense mutations is a big challenge for exome annotation. Predictors of deleteriousness that are most frequently used to filter variants found by next generation sequencing, produce qualitative predictions, but also numerical scores. It has never been tested if these scores correlate with disease severity. Results wANNOVAR, a popular tool that can generate several different types of deleteriousness-prediction scores, was tested on Fabry disease. This pathology, which is caused by a deficit of lysosomal alpha-galactosidase, has a very large genotypic and phenotypic spectrum and offers the possibility of associating a quantitative measure of the damage caused by mutations to the functioning of the enzyme in the cells. Some predictors, and in particular VEST3 and PolyPhen2 provide scores that correlate with the severity of lysosomal alpha-galactosidase mutations in a statistically significant way. Conclusions Sorting disease mutations by severity is possible and offers advantages over binary classification. Dataset for testing and training in silico predictors can be obtained by transient transfection and evaluation of residual activity of mutants in cell extracts. This approach consents to quantitative data for severe, mild and non pathological variants. |
topic |
Rare disease Clinical informatics Variant analysis Bioinformatics Fabry disease |
url |
http://link.springer.com/article/10.1186/s12859-018-2416-7 |
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