Sentence examples for deleterious prediction from inspiring English sources

This analysis showed substantial improvement when compared with classical deleterious prediction methods such as Poly Phen SIFT, MutationTaster and CAROL.

These annotation conflicts can be resolved by focusing only on canonical transcripts for each gene (for example, RefSeqGene), by focusing on the longest transcript in each gene, or by using the most deleterious prediction from all available transcripts.

Overall, we found an average of 3.7 variants (in 80 genes) with deleterious prediction outcome, including a number of novel variants, in individuals with nonsyndromic hearing loss and 1.4 in controls.

Secondly, non-synonymous variants leading to the substitution of an amino acid residue were scored according to the most deleterious prediction of SIFT (Ng and Henikoff, 2002), Polyphen2 (Adzhubei et al., 2010) or MutationTaster (Schwarz et al., 2010).

Input variants were the 17,310 and 14,920 SNP variants contained between the CI interval of Fatq2a (170.5 to 173.03) and Fatq2b (173.3 and 175.6), BioMart settings were set to filter variants containing a tolerated and deleterious prediction between CAST/EiJ and C57BL/6J.

Consequently, we developed a ranking system that classifies homozygous nsSNPs into eight categories according to the overlap of (i) consensus deleterious prediction, (ii) documentation that the SNP causes a disease, and evidence that the SNP is in a gene that has been associated with (iii) a disease or (iv) a quantitative trait.

Prediction counts indicate the number of deleterious predictions (Del count) and conservation predictions (Con count) by six and three programs, respectively.

In addition to the deleterious predictions, protein regions under evolutionary constraint were detected using three evolutionary conservation-based indicators: GERP++ [ 22], phyloP [ 23], and SiPhy [ 24].

An 8-level classification scheme is constructed from the presence/absence of deleterious predictions combined with evidence of association with disease or complex traits.

The notable differences in deleterious predictions given a set of disease-promoting variants found in African American and Caucasian samples suggest these prediction algorithms may have population-specific effects.

In studies of human disease, a significant correlation was observed between the deleterious predictions of single-nucleotide polymorphisms (SNPs) and their association with cancer (Zhu et al. 2004); predicted rare, deleterious SNPs also were shown to be involved in common diseases (Cohen et al. 2004; Smigrodzki et al. 2004).