English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Single nucleotide polymorphism, often abbreviated to SNP, in the genomes of species individuals refers to a variation in a single nucleotide that occurs at a specific position in the genome, where each variation is present to some appreciable degree within a population. In recent years, the research of detection algorithm for SNP has been a hotspot in genomics, computational biology and informatics. Most of SNP detection algorithms are based on sequencing technology of the next generation sequencing (NGS). In this paper, a general overview of detection methods for single nucleotide polymorphism is made to deeply analyze several current mainstream detection algorithms for SNP. It is important for further development of this field of bioinformatics. Introduction In recent years, with the development of bioinformatics and molecular detection technology, the research of single nucleotide polymorphism (SNP) has attracted much attention all over the world [1]. Generally speaking, SNP refers to a DNA sequence polymorphism caused by single-nucleotide variation at the genome level. For a single individual, SNP refers to polymorphic sites in the genome. For the population, SNP can be regarded as the base position with polymorphism in the population [2]. As a genetic variation, SNP can describe the vast majority of differences between individuals and groups of organisms [3]. Therefore, the SNP detection has been widely used in genomic research. The basic processes of SNP detection include genotype resequencing, sequence alignment, SNP detection and filtering of results [4]. Since the vast majority of SNP sites are located in highly interlocking and unbalanced genomic regions, a representative group of SNP sites (Haplotype, known as Haplotype) can be selected as the research object [5], which helps to identify similar polymorphic sites near chromosomes. Due to the importance of SNP sites in biogenetics, the purpose of this paper is to overview the current mainstream detection algorithms and research progress of SNP in academia. Sequence Alignment Nowadays, the DNA sequencing technology has gone through four generations. The first generation of DNA sequence analysis method is based on accurate sequence or genotype [6]. The second generation sequencing technology which is known as high-throughput sequencing technologies, depends on the mass marking nucleotide. The third generation sequencing technology is based on direct observations of DNA replication, and the fourth generation of sequencing technology is based on nanopores single DNA sequencing technology. Compared with the classical first-generation sequencing, the second-generation sequencing technology has the advantages of low experimental cost, low experimental complexity and high output rate. With the development of various algorithms, it has been widely used in biological studies such as genomic DNA sequencing, genetic modification and RNA transcriptome [7]. Sequence alignment is to compare the short sequence obtained by resequencing in contrast to the existing genome sequence (reference) and precisely locate the position of the short sequence on the

A General Overview of Detection Methods for Single Nucleotide Polymorphism