Assessing Pathogenicity PRobability in Arrhythmia by Integrating Statistical Evidence

APPRAISE - Assessing Pathogenicity Probablility in Arrhythmia by Integrating Statistical Evidence - is a Bayesian logistic regression model that integrates multiple lines of evidence to evaluate the probability that a rare variant found in an individual with long QT syndrome is the cause of their disease (manuscript in submission). This evidence includes the and domain containing the variant, variant class, SIFT/Polyphen/Grantham missense predictions, conservation and frequency in population databases (1000 Genomes and Exome Sequencing Project).

Choose a gene and enter the cDNA variant you wish to analyse. If you have a LOD score for the variant's segregation in the family, this can be added to the final probability of pathogencitiy.

Variants should be described as follows (using these default transcripts):

Algorithm Details: Click here for further details of the APPRAISE algorithm including the BUGS model
Reference: Bayesian models for syndrome- and gene-specific probabilities of novel variant pathogenicity, Genome Med. 2015 Jan 28;7(1):5, Ruklisa D, Ware JS, Walsh R, Balding DJ, Cook SA.