Work

Bernoulli mixture models in application to the evaluation of algorithms estimating functionality of missense mutations

Year: 2012

Type: article

Abstract: Background Whole genome and whole exome sequencing projects yield thousands of missense mutations with unknown functionality. Direct estimation of the sensitivity and specificity of bioinformatic algorithms predicting the impact of missense mutations on protein function requires a ‘gold standard’ or set of mutations with known functionality. In the absence of a gold standard, additional statistical methods are needed to estimate the accuracy of these algorithms. It has been shown informative predictions depend on the algorithm and sequence alignment employed and often algorithms disagree as to which mutations are predicted deleterious or neutral [1].

Source: BMC Proceedings

DOI: 10.1186/1753-6561-6-s6-p15

Authors: Stephanie Hicks, Sharon E Plon, Marek Kimmel

Institutions: Rice University, Baylor College of Medicine

Language: English

Topic: Genomics and Rare Diseases

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $2,290

Funders: Cancer Prevention and Research Institute of Texas, National Cancer Institute