CAMITAX: Taxon labels for microbial genomes

Bremges, Andreas; Fritz, Adrian; McHardy, Alice C.

doi:10.1101/532473

Cited by 3 publications

(3 citation statements)

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“…We removed contigs smaller than 1 kb, as well as genome assemblies with a contamination of 5% or more and completeness of 90% or less, as determined with CheckM 74 version 1.011. Newly assembled and database genomes were taxonomically classified with CAMITAX 75 and used as input for microbial community and metagenome data simulation with CAMISIM 76 , based on the from_profile mode for the marine and plant-associated dataset and the de novo mode for the strain madness datasets. All scripts and parameters for these steps are provided in the Supplementary Material and on GitHub (https://github.com/CAMIchallenge/second_challenge_evaluation/tree/master/scripts/data_generation).…”

Section: Genome Sequencing and Assemblymentioning

confidence: 99%

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Critical Assessment of Metagenome Interpretation - the second round of challenges

Meyer

Fritz

Deng

et al. 2021

Preprint

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Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the community-driven initiative for the Critical Assessment of Metagenome Interpretation (CAMI). In its second challenge, CAMI engaged the community to assess their methods on realistic and complex metagenomic datasets with long and short reads, created from ∼1,700 novel and known microbial genomes, as well as ∼600 novel plasmids and viruses. Altogether 5,002 results by 76 program versions were analyzed, representing a 22x increase in results.Substantial improvements were seen in metagenome assembly, some due to using long-read data. The presence of related strains still was challenging for assembly and genome binning, as was assembly quality for the latter. Taxon profilers demonstrated a marked maturation, with taxon profilers and binners excelling at higher bacterial taxonomic ranks, but underperforming for viruses and archaea. Assessment of clinical pathogen detection techniques revealed a need to improve reproducibility. Analysis of program runtimes and memory usage identified highly efficient programs, including some top performers with other metrics. The CAMI II results identify current challenges, but also guide researchers in selecting methods for specific analyses.

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Section: Genome Sequencing and Assemblymentioning

confidence: 99%

“…74 Helmholtz Centre for Infection Research, Braunschweig, Germany. 75 Aarhus University, Aarhus, Denmark. 76 Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany.…”

mentioning

confidence: 99%

Critical Assessment of Metagenome Interpretation - the second round of challenges

Meyer

Fritz

Deng

et al. 2021

Preprint

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“…The reads, contigs and MAGs were run through the MAGinator workflow (v.0.1.16). For comparison purposes the VAMB clusters were annotated with a NCBI Taxonomy ID using CAMITAX 26 . The profile was created with Python 3 and the lineage found using NCBI's lineage taxonomy (https://ftp.ncbi.nlm.nih.gov/pub/taxonomy/new_taxdump/, accessed May 9th 2023).…”

Section: Benchmarking With Opal On Cami's Stimulated Strain-madness D...mentioning

confidence: 99%

MAGinator enables strain-level quantification ofde novoMAGs

Zachariasen,

Russel,

Petersen

et al. 2023

Preprint

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MotivationMetagenomic sequencing has provided great advantages in the characterization of microbiomes, but currently available analysis tools lack the ability to combine strain-level taxonomic resolution and abundance estimation with functional profiling of assembled genomes. In order to define the microbiome and its associations with human health, improved tools are needed to enable comprehensive understanding of the microbial composition and elucidation of the phylogenetic and functional relationships between the microbes.ResultsHere, we present MAGinator, a freely available tool, tailored for the profiling of shotgun metagenomics datasets. MAGinator providesde novoidentification of subspecies-level microbes and accurate abundance estimates of metagenome-assembled genomes (MAGs). MAGinator utilises the information from both gene- and contig-based methods yielding insight into both taxonomic profiles and the origin of genes as well as genetic content, used for inference of functional content of each sample by host organism. Additionally, MAGinator facilitates the reconstruction of phylogenetic relationships between the MAGs, providing a framework to identify clade-level differences within subspecies MAGs.Availability and implementationMAGinator is available as a Python module athttps://github.com/Russel88/MAGinatorContactTrine Zachariasen,trine_zachariasen@hotmail.com

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CAMITAX: Taxon labels for microbial genomes

2020

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Background The number of microbial genome sequences is increasing exponentially, especially thanks to recent advances in recovering complete or near-complete genomes from metagenomes and single cells. Assigning reliable taxon labels to genomes is key and often a prerequisite for downstream analyses. Findings We introduce CAMITAX, a scalable and reproducible workflow for the taxonomic labelling of microbial genomes recovered from isolates, single cells, and metagenomes. CAMITAX combines genome distance–, 16S ribosomal RNA gene–, and gene homology–based taxonomic assignments with phylogenetic placement. It uses Nextflow to orchestrate reference databases and software containers and thus combines ease of installation and use with computational reproducibility. We evaluated the method on several hundred metagenome-assembled genomes with high-quality taxonomic annotations from the TARA Oceans project, and we show that the ensemble classification method in CAMITAX improved on all individual methods across tested ranks. Conclusions While we initially developed CAMITAX to aid the Critical Assessment of Metagenome Interpretation (CAMI) initiative, it evolved into a comprehensive software package to reliably assign taxon labels to microbial genomes. CAMITAX is available under Apache License 2.0 at https://github.com/CAMI-challenge/CAMITAX.

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CAMITAX: Taxon labels for microbial genomes

Cited by 3 publications

References 69 publications

Critical Assessment of Metagenome Interpretation - the second round of challenges

Critical Assessment of Metagenome Interpretation - the second round of challenges

MAGinator enables strain-level quantification ofde novoMAGs

CAMITAX: Taxon labels for microbial genomes

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