| Summary: | Prashanth Suravajhala,1 Alfredo Benso2 1Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark; 2Department of Control and Computer Engineering, Politecnico di Torino, Torino, Italy Abstract: 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. Keywords: clinical mastitis, single-nucleotide polymorphisms, variants, associations, diseases, linkage disequilibrium, GWAS
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