CAMMiQ

CAMMiQ identifies and quantifies microbial species and strains from high-throughput sequencing (HTS) reads to estimate microbial abundance.


Key Features:

  • Combinatorial approach: Utilizes arbitrary-length, doubly-unique substrings (substrings found in exactly two genomes) to improve specificity of read classification between closely related strains.
  • Efficient indexing and query resolution: Constructs a compact index of sparsified subsets of the shortest unique and doubly-unique substrings from each genome to manage large genomic databases, including bacterial and viral genomes from NCBI RefSeq.
  • Combinatorial optimization: Employs a combinatorial optimization formulation to resolve ambiguities associated with doubly-unique substrings during read assignment and abundance estimation.
  • Species- and strain-level quantification: Estimates relative abundance at both species and strain resolution from HTS reads.
  • Compatibility with scRNA-seq: Distinguishes closely related microbial strains in single-cell RNA sequencing (scRNA-seq) data, including separately infected Salmonella strains.
  • Performance and resource efficiency: Demonstrates superior accuracy on simulated and real datasets, including complex bacterial genomes, while maintaining computational efficiency comparable to other tools.

Scientific Applications:

  • Microbiome studies: Determining composition and dynamics of microbial communities within environments or host organisms.
  • Infectious disease research: Identifying pathogenic strains and quantifying their prevalence and distribution.
  • Genomic epidemiology: Tracking the spread and evolution of microbial strains in populations.

Methodology:

Builds a compact index from unique and doubly-unique substrings within user-specified length ranges using sparsified subsets of the shortest unique and doubly-unique substrings per genome, then resolves queries by identifying genomic origins of HTS reads and estimating relative abundances via a combinatorial optimization formulation to disambiguate doubly-unique substring assignments.

Topics

Details

License:
MIT
Tool Type:
command-line tool
Programming Languages:
C++
Added:
1/18/2021
Last Updated:
2/6/2021

Operations

Publications

Zhu K, Robinson W, Schäffer AA, Xu J, Ruppin E, Ergun AF, Ye Y, Sahinalp SC. Strain Level Microbial Detection and Quantification with Applications to Single Cell Metagenomics. Unknown Journal. 2020. doi:10.1101/2020.06.12.149245.