CONSULT

CONSULT identifies and removes contaminant sequencing reads by matching k-mers from genomic sequencing reads to large reference libraries to improve accuracy of genome skims and organelle (mitochondrial) assemblies.

Key Features:

• Locality-Sensitive Hashing (LSH): Employs locality-sensitive hashing for efficient k-mer extraction and rapid comparison of sequencing reads against reference k-mer sets.
• User-Specified Hamming Distance: Tests whether extracted k-mers fall within a user-defined Hamming distance of reference k-mers, allowing adjustment of sensitivity and specificity.
• High Sensitivity and Specificity: Demonstrates higher true-positive rates and lower false-positive rates compared to Kraken-II for contamination detection.
• Large Reference Libraries: Handles extensive reference libraries accommodating tens of thousands of microbial species for comprehensive contamination screening.

Scientific Applications:

• Low-Coverage Genome Sequencing (Skimming): Detects and removes contaminant reads from low-coverage genome skims to enable assembly of organelle genomes and computation of genomic distances from unassembled reads.
• Organelle vs. Nuclear Read Distinction: Differentiates organelle and nuclear reads to support accurate mitochondrial genome assemblies derived from skimming approaches.
• Improved Distance Calculations: Improves accuracy of genomic distance calculations in genome skims, supporting phylogenetic and evolutionary analyses.

Methodology:

K-mer-based read-matching using locality-sensitive hashing (LSH) with k-mer extraction from sequencing reads and testing matches within a user-defined Hamming distance against reference k-mer sets.