Nature MethodsBioinformaticsPeer-reviewed journal article
Critical Assessment of Metagenome Interpretation - the second round of challenges
Fernando MeyeriD, Adrian FritziD, Zhi-Luo DengiD, David KoslickiiD, Till Robin LeskeriD, Alexey A. GurevichiD, Gary RobertsoniD, Mohammed AlseriD, Dmitry AntipoviD, Francesco BeghiniiD, Denis Bertrand, Jaqueline BritoiD, C. Titus BrowniD, Jan P. BuchmanniD, Aydın BuluçiD, Bo CheniD, Rayan ChikhiiD, Philip T. L. C. ClauseniD, Alexandru Cristian, Piotr Wojciech DąbrowskiiD, Aaron E. DarlingiD, Rob S EganiD, Eleazar EskiniD, Evangelos GeorganasiD, Eugene Goltsman, , Till StrowigiD
Abstract
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.
- assay: metagenomics
- research focus: benchmarking
- research focus: software / tool
- research focus: variant calling
- research focus: genome assembly
- approach: statistical model
- approach: benchmark study
- Citations
- 371
- FWCI
- 23.83
- Field percentile
- top 1%
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