FAMeS

Metagenomics is a rapidly emerging field of research for studying microbial communities. To evaluate methods currently used to process metagenomic sequences, simulated datasets of varying complexity were constructed by combining sequencing reads randomly selected from 113 isolate genomes. These datasets were designed to model real metagenomes in terms of complexity and phylogenetic composition. Assembly, gene prediction and binning, employing methods commonly used for the analysis of metagenomic datasets at the DOE JGI, were performed. This site provides access to the simulated datasets, and aims to facilitate standardized benchmarking of tools for metagenomic analysis.

We would like to invite members of the scientific community to use these datasets, to evaluate new methods, and submit their results in order to create a comprehensive resource for the comparison of methods.

If you use the data or results found on this site please cite the following paper:
Use of simulated data sets to evaluate the fidelity of metagenomic processing methods
Konstantinos Mavromatis, Natalia Ivanova, Kerrie Barry, Harris Shapiro, Eugene Goltsman, Alice C McHardy, Isidore Rigoutsos, Asaf Salamov, Frank Korzeniewski, Miriam Land, Alla Lapidus, Igor Grigoriev, Paul Richardson, Philip Hugenholtz, Nikos C Kyrpides
Nature Methods 2007 Jun;4(6):495-500.

Datasets and Methods

Assembly Method Comparison

Binning Method Comparison

Gene Function Prediction Method Comparison

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