Ranking insertion, deletion and nonsense mutations based on their effect on genetic information.

ABSTRACT:

Background

Genetic variations contribute to normal phenotypic differences as well as diseases, and new sequencing technologies are greatly increasing the capacity to identify these variations. Given the large number of variations now being discovered, computational methods to prioritize the functional importance of genetic variations are of growing interest. Thus far, the focus of computational tools has been mainly on the prediction of the effects of amino acid changing single nucleotide polymorphisms (SNPs) and little attention has been paid to indels or nonsense SNPs that result in premature stop codons.

Results

We propose computational methods to rank insertion-deletion mutations in the coding as well as non-coding regions and nonsense mutations. We rank these variations

SUBMITTER: Zia A 

PROVIDER: S-EPMC3155974 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature