BICEP: an extension to indels and copy number variants for rare variant prioritisation in pedigree analysis

Read full text
Authors: Cathal Ormond, Niamh Ryan, Aiden P. Corvin, Elizabeth A. Heron
Cited by: 1
References: 27

Abstract

BICEP is a Bayesian inference model that evaluates how likely a rare variant is to be causal for a genomic trait in pedigree-based analyses. The original prior model in BICEP was designed for single nucleotide variants only. Here, we have developed an extension of the prior models for more comprehensive genomic analysis to include indels and copy number variants. We benchmark the performance of these new priors and show comparable performance accuracy with the existing single nucleotide variant prior model. For copy number variants we evaluate four different input predictors to the models and recommend the best performing ones as the default. Availability and implementation: the updated prior models have been implemented in the current version of BICEP available from: https://github.com/cathaloruaidh/BICEP.

Fields of Study & Subjects

Genetic Associations and Epidemiology Genomics and Rare Diseases Genomic variations and chromosomal abnormalities

Publication details

Journal / source
bioRxiv (Cold Spring Harbor Laboratory)
Publisher
openRxiv
Publication date
11 March 2026
Language
EN
Document type
Preprint