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Prioritizing single-nucleotide polymorphisms and variants associated with clinical mastitis

Next-generation sequencing technology has provided resources to easily explore and identify candidate single-nucleotide polymorphisms (SNPs) and variants. However, there remains a challenge in identifying and inferring the causal SNPs from sequence data. A problem with different methods that predict...

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Detalles Bibliográficos
Autores principales: Suravajhala, Prashanth, Benso, Alfredo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5473491/
https://www.ncbi.nlm.nih.gov/pubmed/28652783
http://dx.doi.org/10.2147/AABC.S123604
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author Suravajhala, Prashanth
Benso, Alfredo
author_facet Suravajhala, Prashanth
Benso, Alfredo
author_sort Suravajhala, Prashanth
collection PubMed
description Next-generation sequencing technology has provided resources to easily explore and identify candidate single-nucleotide polymorphisms (SNPs) and variants. However, there remains a challenge in identifying and inferring the causal SNPs from sequence data. A problem with different methods that predict the effect of mutations is that they produce false positives. In this hypothesis, we provide an overview of methods known for identifying causal variants and discuss the challenges, fallacies, and prospects in discerning candidate SNPs. We then propose a three-point classification strategy, which could be an additional annotation method in identifying causalities.
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spelling pubmed-54734912017-06-26 Prioritizing single-nucleotide polymorphisms and variants associated with clinical mastitis Suravajhala, Prashanth Benso, Alfredo Adv Appl Bioinform Chem Hypothesis Next-generation sequencing technology has provided resources to easily explore and identify candidate single-nucleotide polymorphisms (SNPs) and variants. However, there remains a challenge in identifying and inferring the causal SNPs from sequence data. A problem with different methods that predict the effect of mutations is that they produce false positives. In this hypothesis, we provide an overview of methods known for identifying causal variants and discuss the challenges, fallacies, and prospects in discerning candidate SNPs. We then propose a three-point classification strategy, which could be an additional annotation method in identifying causalities. Dove Medical Press 2017-06-12 /pmc/articles/PMC5473491/ /pubmed/28652783 http://dx.doi.org/10.2147/AABC.S123604 Text en © 2017 Suravajhala and Benso. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
spellingShingle Hypothesis
Suravajhala, Prashanth
Benso, Alfredo
Prioritizing single-nucleotide polymorphisms and variants associated with clinical mastitis
title Prioritizing single-nucleotide polymorphisms and variants associated with clinical mastitis
title_full Prioritizing single-nucleotide polymorphisms and variants associated with clinical mastitis
title_fullStr Prioritizing single-nucleotide polymorphisms and variants associated with clinical mastitis
title_full_unstemmed Prioritizing single-nucleotide polymorphisms and variants associated with clinical mastitis
title_short Prioritizing single-nucleotide polymorphisms and variants associated with clinical mastitis
title_sort prioritizing single-nucleotide polymorphisms and variants associated with clinical mastitis
topic Hypothesis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5473491/
https://www.ncbi.nlm.nih.gov/pubmed/28652783
http://dx.doi.org/10.2147/AABC.S123604
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