优先考虑与临床乳腺炎相关的单核苷酸多态性和变异。

Q2 Biochemistry, Genetics and Molecular Biology
Advances and Applications in Bioinformatics and Chemistry Pub Date : 2017-06-12 eCollection Date: 2017-01-01 DOI:10.2147/AABC.S123604
Prashanth Suravajhala, Alfredo Benso
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引用次数: 6

摘要

新一代测序技术为探索和鉴定候选单核苷酸多态性(snp)和变异提供了资源。然而,从序列数据中识别和推断因果snp仍然是一个挑战。预测突变影响的不同方法的一个问题是,它们会产生假阳性。在这个假设中,我们概述了已知的识别因果变异的方法,并讨论了识别候选snp的挑战、谬误和前景。然后,我们提出了一种三点分类策略,这可能是识别因果关系的另一种注释方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Prioritizing single-nucleotide polymorphisms and variants associated with clinical mastitis.

Prioritizing single-nucleotide polymorphisms and variants associated with clinical mastitis.

Prioritizing single-nucleotide polymorphisms and variants associated with clinical mastitis.

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 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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来源期刊
Advances and Applications in Bioinformatics and Chemistry
Advances and Applications in Bioinformatics and Chemistry Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (miscellaneous)
CiteScore
6.50
自引率
0.00%
发文量
7
审稿时长
16 weeks
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