{"title":"优先考虑与临床乳腺炎相关的单核苷酸多态性和变异。","authors":"Prashanth Suravajhala, Alfredo Benso","doi":"10.2147/AABC.S123604","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":53584,"journal":{"name":"Advances and Applications in Bioinformatics and Chemistry","volume":"10 ","pages":"57-64"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2147/AABC.S123604","citationCount":"6","resultStr":"{\"title\":\"Prioritizing single-nucleotide polymorphisms and variants associated with clinical mastitis.\",\"authors\":\"Prashanth Suravajhala, Alfredo Benso\",\"doi\":\"10.2147/AABC.S123604\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":53584,\"journal\":{\"name\":\"Advances and Applications in Bioinformatics and Chemistry\",\"volume\":\"10 \",\"pages\":\"57-64\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.2147/AABC.S123604\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances and Applications in Bioinformatics and Chemistry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2147/AABC.S123604\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2017/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"Biochemistry, Genetics and Molecular Biology\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances and Applications in Bioinformatics and Chemistry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2147/AABC.S123604","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2017/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
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.