BiERapp

BiERapp prioritizes candidate disease-causing variants from whole exome sequencing data to identify causal mutations in familial and sporadic genetic diseases and tumor samples.

Key Features:

• Variant analysis: Processes lists of predicted variants including nucleotide substitutions and insertions/deletions (indels) from affected individuals or tumor samples alongside controls.
• Inheritance mode filtering: Filters variants according to user-defined modes of inheritance to retain variants that segregate with the disease phenotype in family studies.
• Integration of population and pathogenicity data: Incorporates allelic frequencies from general population databases and damaging/predicted pathogenicity scores to refine candidate variant lists.
• Large-scale project application (CIBERER): Demonstrated applicability to high-throughput studies, as exemplified by analysis of over 800 exomes within the Spanish Network for Research in Rare Diseases (CIBERER) project.

Scientific Applications:

• Familial disease gene discovery: Prioritizes variants segregating with disease in family-based whole exome sequencing studies to support identification of causative genes.
• Cancer genomics: Aids identification of somatic driver variants by comparing tumor samples to controls and filtering by frequency and predicted impact.
• Rare disease research: Reduces candidate variant lists to facilitate discovery of novel disease-related genes in rare genetic disorders.

Methodology:

Systematic variant filtering based on inheritance patterns, comparison of affected/tumor samples with controls, population allele-frequency thresholds, and predicted pathogenicity/damaging scores applied to lists of nucleotide substitutions and indels.