Taxonomic classification Tools

Program for the taxonomic assignment of high-throughput sequencing reads, e.g., Illumina or Roche/454, from whole-genome sequencing of metagenomic DNA. Reads are directly assigned to taxa using the NCBI taxonomy and a reference database of protein sequences from Bacteria, Archaea, Fungi, microbial eukaryotes and viruses.

Kraken 2 is the newest version of Kraken, a taxonomic classification system using exact k-mer matches to achieve high accuracy and fast classification speeds. This classifier matches each k-mer within a query sequence to the lowest common ancestor (LCA) of all genomes containing the given k-mer. The k-mer assignments inform the classification algorithm. Any assumption that Kraken’s raw read assignments can be directly translated into species or strain-level abundance estimates is flawed. Bracken (Bayesian Reestimation of Abundance after Classification with KrakEN), estimates species abundances in metagenomics samples by probabilistically re-distributing reads in the taxonomic tree. (Lu, Jennifer et al. “Bracken: estimating species abundance in metagenomics data.”)

KrakenTools is a suite of scripts to be used alongside the Kraken, KrakenUniq, Kraken 2, or Bracken programs. These scripts are designed to help Kraken users with downstream analysis of Kraken results.

Metagenome Analysis Software - MEGAN (MEtaGenome ANalyzer) is a new computer program that allows laptop analysis of large metagenomic datasets. In a preprocessing step, the set of DNA reads (or contigs) is compared against databases of known sequences using BLAST or another comparison tool. MEGAN can then be used to compute and interactively explore the taxonomical content of the dataset, employing the NCBI taxonomy to summarize and order the results.

Computational tool for profiling the composition of microbial communities from metagenomic shotgun sequencing data.

Metagenomic operational taxonomic units (mOTUs) enable high-accuracy taxonomic profiling of known (sequenced) and unknown microorganisms at species-level resolution from shotgun metagenomic or metatranscriptomic data. The method clusters single-copy phylogenetic marker gene sequences from metagenomes and reference genomes into mOTUs to quantify their abundances in meta-omics data with very high precision and recall.