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Dataset Information

SeqEM: an adaptive genotype-calling approach for next-generation sequencing studies.


ABSTRACT:

Motivation

Next-generation sequencing presents several statistical challenges, with one of the most fundamental being determining an individual's genotype from multiple aligned short read sequences at a position. Some simple approaches for genotype calling apply fixed filters, such as calling a heterozygote if more than a specified percentage of the reads have variant nucleotide calls. Other genotype-calling methods, such as MAQ and SOAPsnp, are implementations of Bayes classifiers in that they classify genotypes using posterior genotype probabilities.

Results

Here, we propose a novel genotype-calling algorithm that, in contrast to the other methods, estimates parameters underlying the posterior probabilities in an adaptive way rather than arbitrarily specifying them a prior

SUBMITTER: Martin ER 

PROVIDER: S-EPMC2971572 | biostudies-literature | 2010 Nov

REPOSITORIES: biostudies-literature