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Single Nucleotide Polymorphisms-SNPs01:05

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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
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MAFsnp: A Multi-Sample Accurate and Flexible SNP Caller Using Next-Generation Sequencing Data.

Jiyuan Hu1, Tengfei Li2, Zidi Xiu1

  • 1State Key Laboratory of Genetic Engineering and Institute of Biostatistics, School of Life Sciences, Fudan University, 220 Handan Road, Shanghai 200433, P. R. China.

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|August 27, 2015
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Summary

MAFsnp is a novel frequentist statistical method for accurately calling single nucleotide polymorphisms (SNPs) from next-generation sequencing (NGS) data. It provides p-values and better false discovery rate control than existing Bayesian methods.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Statistical Genetics

Background:

  • Existing single nucleotide polymorphism (SNP) callers for next-generation sequencing (NGS) data predominantly use Bayesian frameworks.
  • There is a lack of SNP callers that provide p-values within a frequentist statistical framework.

Purpose of the Study:

  • To develop a novel, accurate, and flexible frequentist method for SNP calling from NGS data.
  • To introduce a new statistical approach that generates p-values for SNP detection.

Main Methods:

  • Developed MAFsnp, a Multiple-sample based Accurate and Flexible algorithm for calling SNPs.
  • Utilized an estimated likelihood ratio test (eLRT) statistic and modeled its distribution using a novel two-parameter mixture distribution.
  • Implemented p-value calculation and multiple-testing correction for false discovery rate (FDR) control.

Main Results:

  • MAFsnp demonstrated superior control of FDR compared to existing SNP callers on simulated data.
  • The method showed improved calling accuracy on two real NGS datasets.
  • An R package 'MAFsnp' is available for public use.

Conclusions:

  • MAFsnp successfully fills the gap for a frequentist SNP caller in NGS data analysis.
  • The novel statistical approach provides accurate SNP detection with robust FDR control.
  • MAFsnp offers a valuable alternative for genomic variant calling.