Home > Papers

 
 
A novel genotyping algorithm for SNP detection using next generation sequencing data
Huang Gongyi, You Na
*Correspondence author
#Submitted by
Subject:
Funding: 高等学校博士学科点专项科研基金（No.20120171120006）
Opened online:28 October 2015
Accepted by: none
Citation: Huang Gongyi, You Na.A novel genotyping algorithm for SNP detection using next generation sequencing data[OL]. [28 October 2015] http://en.paper.edu.cn/en_releasepaper/content/4657982
 
 
Genotyping the population using next generation sequencing data is essentially important for the rare variant detection. In order to distinguish the genomic structural variation from sequencing error, a statistical model is proposed, which involves the genotype effect through a latent variable to depict the distribution of non-reference allele frequency data among different samples and different genome loci, while decomposing the sequencing error into sample effect and positional effect. An ECM algorithm is implemented to estimate the model parameters, and then the genotypes are inferred based on the posterior probabilities. The performances of our proposed method are investigated via simulations and a real data analysis. Comparing to the existing methods, it is shown that our method can make less genotype-call errors.
Keywords:Biostatistics; empirical Bayes; Next generation sequencing data; Genotyping
 
 
 

For this paper
  • ● PDF (0B)
  • ● Revision 0 　　
  • ● Print this paper
  • ● Recommend this paper to a friend
  • ● Add to my favorite list

    Saved Papers

    Please enter a name for this paper to be shown in your personalized Saved Papers list

Tags
Add yours

Related Papers

Statistics
PDF Downloaded 49
Bookmarked 0
Recommend 0
Comments Array
Submit your papers