Bracken

Bracken re-estimates taxonomic abundances from Kraken 1, KrakenUniq, or Kraken 2 classification output to provide accurate species- and genus-level abundance profiles from shotgun high-throughput DNA sequencing reads.


Key Features:

  • Kraken integration: Uses read-level classifications produced by Kraken 1, KrakenUniq, or Kraken 2 as the input basis for abundance estimation.
  • Bayesian re-estimation: Applies a Bayesian approach to reassign and redistribute reads from Kraken assignments to compute taxon abundances.
  • Genomic adjustment: Incorporates genomic information to correct for biases in read distribution across different taxa.
  • Taxonomic resolution: Produces abundance estimates at multiple hierarchical levels, explicitly including species and genus.
  • Input data: Operates on raw shotgun metagenomic high-throughput DNA sequencing reads.
  • Complex-sample sensitivity: Capable of producing reliable abundance estimates in samples containing multiple near-identical species.

Scientific Applications:

  • Microbial community profiling: Quantifies organismal composition of environmental or host-associated microbiomes using shotgun sequencing data.
  • Fine-resolution abundance estimation: Provides species- and genus-level abundance profiles beyond marker-gene surveys such as 16S ribosomal RNA gene sequencing.
  • Population structure analysis: Facilitates comparative analyses of microbial population structure and dynamics across samples.

Methodology:

Bracken uses Kraken classifications as the foundation and applies a Bayesian re-estimation procedure that incorporates genomic information to adjust read distribution and compute taxon abundances.

Topics

Collections

Details

License:
GPL-3.0
Tool Type:
command-line tool
Operating Systems:
Linux
Programming Languages:
Perl, Python
Added:
8/20/2017
Last Updated:
6/11/2025

Operations

Data Inputs & Outputs

Statistical calculation

Publications

Lu J, Breitwieser FP, Thielen P, Salzberg SL. Bracken: estimating species abundance in metagenomics data. PeerJ Computer Science. 2017;3:e104. doi:10.7717/peerj-cs.104. PMID:40271438. PMCID:PMC12016282.

Funding: - US National Institutes of Health: R01-GM083873, R01-HG006677 - US Army Research Office: W911NF-1410490

Documentation

Links

Related Tools

kraken2
Relation: uses