JointSLM

JointSLM detects copy number variants (CNVs) by jointly analyzing read depth of coverage (DOC) from multiple high-throughput sequencing (HTS) samples to identify recurrent CNV regions across individuals for population genetics and disease studies.

Key Features:

• Simultaneous Multi-Sample Analysis: Processes and compares read depth of coverage (DOC) across multiple samples concurrently to detect common CNVs shared among individuals.
• High-Resolution Detection: Detects recurrent CNV regions as small as 500 base pairs (bp).
• Population Genetics Clustering: Clusters individuals via hierarchical clustering of identified CNV regions to reflect genetic ancestry and diversity within populations.
• Performance Validation: Validated on synthetic and real datasets, including analysis of chromosome one from eight genomes that identified 3,000 recurrent CNV regions and segregated individuals by ancestry.

Scientific Applications:

• Genomic Variation Studies: Identifies recurrent CNV regions to characterize genetic variability within human populations and inform evolutionary biology and population genetics.
• Complex Disease Analysis: Detects small-scale CNVs that may contribute to complex diseases.
• Ancestry and Evolutionary Studies: Segregates individuals based on genetic ancestry through hierarchical clustering of identified CNV regions for evolutionary analyses.

Methodology:

Processes DOC data derived from HTS platforms aligned to the human reference genome to detect common/recurrent CNVs among multiple samples and applies hierarchical clustering of identified CNV regions.