KCOSS

KCOSS counts k-mers in assembled genomes and sequencing datasets to compute k-mer frequency distributions for genome complexity assessment, comparative genomics, metagenomics, and phylogenetic analyses.

Key Features:

• Ultra-Fast Performance: Implements a novel algorithm that leverages segmented Bloom filters, lock-free queues, lock-free thread pools, and cuckoo hash tables to accelerate k-mer counting.
• Optimized Resource Utilization: Reduces memory and disk usage via recycling memory blocks and merging consecutive first-occurrence k-mers into C-reads.
• Asynchronous Disk Writing: Writes sets of C-reads to disk asynchronously to overlap I/O with computation and reduce processing time.
• Versatile Application: Calculates k-mer frequencies for both assembled genomes and sequencing datasets.

Scientific Applications:

• Genomic Complexity Analysis: Provides k-mer frequency distributions to assess genome complexity and structural features.
• Comparative Genomics: Enables efficient cross-genome k-mer counting to support comparative analyses and detection of genomic variation.
• Metagenomics: Processes large metagenomic sequencing datasets to profile community composition via k-mer frequencies.
• Phylogenetic Studies: Supplies k-mer frequency data that can be used in phylogenetic inference and evolutionary analyses.

Methodology:

Uses segmented Bloom filters, lock-free queues and thread pools, cuckoo hash tables, recycling of memory blocks, merging consecutive first-occurrence k-mers into C-reads, and asynchronous writing of C-reads to disk.