Bracken: estimating species abundance in metagenomics data
By Jennifer Lu, Florian P. Breitwieser, P. Thielen, Steven L. Salzberg. bioRxiv, 2016
1,926 citations recorded by the source corpus.
We describe a new, highly accurate statistical method that computes the abundance of species in DNA sequences from a metagenomics sample. Bracken (Bayesian Reestimation of Abundance after Classification with KrakEN) uses the taxonomy labels assigned by Kraken, a highly accurate metagenomics classification algorithm, to estimate the number of reads originating from each species present in a sample. Kraken classifies reads to the best matching location in the taxonomic tree, but does not estimate abundances of species. We use the Kraken database itself to derive probabilities that describe how much sequence from each genome is shared with other genomes in the database, and combine this information with the assignments for a particular sample to estimate abundance at the species level, the genus level, or above. Combined with the Kraken classifier, Bracken produces accurate species-and genus-level abundance estimates even when a sample contains multiple near-identical species.
Subfields: Ecology, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/dcffb78603f9c2cbb4c03fce65f587758db38e12
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Ecology
- Florian P. Breitwieser
- Jennifer Lu
- Steven L. Salzberg
- Ben Langmead
- Derrick E. Wood
- Curtis Huttenhower
- Nicola Segata
- G. Uritskiy
In Molecular Biology
- Florian P. Breitwieser
- Steven L. Salzberg
- Jennifer Lu
- Curtis Huttenhower
- Ben Langmead
- Nicola Segata
- Derrick E. Wood
- Eric A. Franzosa
Citations in the corpus
- Metagenome analysis using the Kraken software suite (2022, methodology): “Following characterization of the original data, downstream analyses may include (4) statistical methods for comparing the microbial compositions of different environments or (5) visualization methods for understanding microbial compositions.”
- MetaWRAP—a flexible pipeline for genome-resolved metagenomic data analysis (2018, background): “It should be noted that while Kraken is fast, post-classification standardization may be needed to obtain a more accurate community composition estimate [38].”
- Improved metagenomic analysis with Kraken 2 (2019, methodology): “…introduce Kraken 2, which provides a major reduction in memory usage as well as faster classification, a spaced seed searching scheme, a translated search mode for matching in amino acid space, and continued compatibility with the Bracken [14] species-level sequence abundance estimation algorithm.”
- A review of methods and databases for metagenomic classification and assembly (2019, background): “Bracken [94] is an extension of Kraken that esti-”
- Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3 (2020, background): “Most such methods focus on addressing a single profiling task within (most often) metagenomes, such as taxonomic profiling (Lu et al., 2017; Milanese et al., 2019; Truong et al., 2015; Wood et al., 2019), strain identification (Luo et al.”
- American Gut: an Open Platform for Citizen Science Microbiome Research (2018, neutral): “0 (104) to estimate the relative abundance of species-level taxa.”
- DNA Sequencing as a Tool to Monitor Marine Ecological Status (2017, background): “…estimation of organism abundance based on normalized read counts of clade-specific marker genes (Segata et al., 2012; Sohn et al., 2014), polymorphisms in universal markers (Luo et al., 2015), or accounting for incorrect taxonomic classification through probabilistic models (Lu et al., 2017).”