SNPest: a probabilistic graphical model for estimating genotypes.

ABSTRACT:

Background

As the use of next-generation sequencing technologies is becoming more widespread, the need for robust software to help with the analysis is growing as well. A key challenge when analyzing sequencing data is the prediction of genotypes from the reads, i.e. correct inference of the underlying DNA sequences that gave rise to the sequenced fragments. For diploid organisms, the genotyper should be able to predict both alleles in the individual. Variations between the individual and the population can then be analyzed by looking for SNPs (single nucleotide polymorphisms) in order to investigate diseases or phenotypic features. To perform robust and high confidence genotyping and SNP calling, methods are needed that take the technology specific limitations into account and can

SUBMITTER: Lindgreen S 

PROVIDER: S-EPMC4203901 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature