Sentence examples for multifactorial likelihood analyses from inspiring English sources

First, the splicing aberrations were predicted with bioinformatic splicing software [ 13], and second, although one of the aberrant transcripts (Δ10) has been reported among naturally occurring MLH1 splice transcripts, the clinical data associated with these variants are also indicative of pathogenicity as demonstrated by the results of previous multifactorial likelihood analyses [ 13].

We have compared the results from multifactorial likelihood analysis with those from several functional analyses for the four BRCA1 sequence variants A1708E, G1738R, R1699Q, and A1708V.

Thompson BA, et al. A multifactorial likelihood model for MMR gene variant classification incorporating probabilities based on sequence bioinformatics and tumor characteristics: a report from the Colon Cancer Family Registry.

Phylogenetic maximum likelihood analyses were performed with RAxML v.7.0.4 [28].

Maximum parsimony and maximum likelihood analyses were carried out.

Similar conclusions were reached using Maximum Likelihood analyses.

We present our comparison of multifactorial likelihood predictions of pathogenicity and functional analysis of these BRCA1 variants.

JM performed the maximum likelihood analyses.

The study included one variant we had previously classified as pathogenic by multifactorial likelihood analysis (G1738R) and three variants that remained unclassified after multifactorial analysis (R1699Q, A1708V, and A1708E) [ 3- 5].

Our results suggest that the addition of tumour immunohistochemical expression can add value to the classification of likely causal BRCA1 variants using multifactorial likelihood analysis and that functional assays are a useful adjunct to multifactorial analysis.

In the case of BRCA1 A1708E, which was previously classified as a UV using multifactorial likelihood analysis based on limited data, revised multifactorial analysis yielded a posterior probability of pathogenicity of 99%.