MoChA

MoChA detects mosaic chromosomal alterations (mCAs) from phased VCF files using B Allele Frequency (BAF), Log R Ratio (LRR), and allelic depth (AD) to identify clonal mosaicism in genetic studies.

Key Features:

• bcftools extension: Functions as an extension to bcftools to analyze phased VCF input for mCA detection.
• Phased VCF and data types: Processes phased VCF files and leverages B Allele Frequency (BAF), Log R Ratio (LRR), and allelic depth (AD) for detection.
• Segmental duplication filtering: Identifies variants within segmental duplications characterized by low divergence (<2%), high missingness (>2%), excess heterozygosity (p<1e-6), and unexpected sex correlation (p<1e-6).
• Long-range phasing: Incorporates long-range phase information to increase sensitivity for detecting chromosomal alterations.
• Copy-number event calling: Calls duplications, deletions, and copy-number neutral loss of heterozygosity (CNN-LOH) and reports indeterminate copy-number states.

Scientific Applications:

• Clonal mosaicism studies: Detects mCAs to study clonal mosaicism across individuals and tissues.
• Aging and cancer research: Used to investigate associations between mCAs and aging- or cancer-related processes.
• Longevity and population studies (New England Centenarian Study): Applied to 338 individuals from the New England Centenarian Study using genome-wide genotypes from blood DNA, detecting chromosomal alteration events in 180 individuals, including 165 duplications, 97 deletions, 9 copy-number neutral LOH, 42 indeterminate copy-number events, and 236 events in individuals aged 100 and older.

Methodology:

Operates as a bcftools extension on phased VCFs, leveraging BAF, LRR, and AD, incorporating long-range phasing, and applying segmental duplication filters with thresholds for divergence (<2%), missingness (>2%), heterozygosity (p<1e-6), and sex correlation (p<1e-6).