seqfam

seqfam performs analysis of next-generation sequencing (NGS) DNA data in pedigreed familial cohorts to identify rare causal genetic variants using Python and the Pandas library.

Key Features:

• Pedigree Verification: Verifies pedigree information by mapping pedigrees and kinship coefficients to expected and observed degrees of relationship.
• Monte Carlo Gene Dropping: Performs Monte Carlo simulations for gene dropping to model inheritance patterns across generations.
• Regression-Based Gene Burden Testing: Implements regression-based gene burden tests and supports customized grouping and aggregation of variants to improve power for detecting rare causal variants.
• Variant Segregation Analysis: Identifies variants that segregate with affection status within families by applying user-defined rules for variant occurrence patterns.
• MapReduce Script Generation: Generates scripts for MapReduce-pattern execution on compute clusters to scale analyses of large NGS datasets.

Scientific Applications:

• Rare Variant Discovery: Detects rare genetic variants potentially causal for diseases or traits in familial NGS data.
• Familial Segregation Studies: Maps variant segregation with affection status across pedigrees to support identification of causal variants.
• Pedigree Quality Control: Validates pedigree and kinship consistency for familial genetic studies.
• Scalable NGS Cohort Analysis: Enables large-scale analyses of NGS cohorts via MapReduce script generation for cluster execution.

Methodology:

Implements pedigree verification via kinship coefficient mapping, Monte Carlo gene-dropping simulations, regression-based gene burden testing with variant grouping, variant segregation analysis using user-defined occurrence rules, and MapReduce script generation; implemented in Python using Pandas.