BICEP: an extension to indels and copy number variants for rare variant prioritisation in pedigree analysis
Year: 2026
Type: article
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. This is a limitation as other types of rare variants are known to influence Mendelian and complex traits. 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. We have described an extension of the original BICEP model to other classes of variants important for genomic traits. The updated prior models have been implemented in the current version of BICEP available from the project GitHub: https://github.com/cathaloruaidh/BICEP .
Source: BMC Bioinformatics
Institution: Trinity College Dublin
Language: English
Topic: Genomics and Rare Diseases
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,990
OpenAlex ID: W7135095160