| Version | MAJ | FROGS | ||
| 0.0.6 | Download | Doc |
Find Rapidly OTUs with Galaxy Solution: FROGS is a galaxy/CLI workflow designed to produce an OTU count matrix from high depth sequencing amplicon data. This workflow is focused on: - User-friendliness with the integration in galaxy and lots of rich graphic outputs - Accuracy with a clustering without global similarity threshold, the management of multi-affiliations and management of separated PCRs in the chimera removal step - Speed with fast algorithms and an easy to use parallelisation - Scalability with algorithms designed to support the data growth
Remarque
| Run Unix # | Run Web # |
| Version | MAJ | MaxBin | ||
| 2.2.1 | 2017-01-17 | Download | Doc |
MaxBin is a software for binning assembled metagenomic sequences based on an Expectation-Maximization algorithm. Users could understand the underlying bins (genomes) of the microbes in their metagenomes by simply providing assembled metagenomic sequences and the reads coverage information or sequencing reads. For users' convenience MaxBin will report genome-related statistics, including estimated completeness, GC content and genome size in the binning summary page. Users could use MEGAN or similar software on MaxBin bins to find out the taxonomy of each bin after the binning process is finished.
Remarque
| Run Unix # run_MaxBin.pl -contig (contig file) -out (output file) | Run Web # |
| Version | MAJ | megan | ||
| 5.10.6 | 2015-07-12 | Download | Doc |
MEGAN - Metagenome Analysis Software
Remarque
| Run Unix # megan | Run Web # |
| Version | MAJ | MetaSim | ||
| 0.9.5 | 2010-09-28 | Download | Doc |
MetaSim - A Sequencing Simulator for Genomics and Metagenomics
Remarque f you use this program for your own research please cite our software. Publication: Richter DC, Ott F, Auch AF, Schmid R, Huson DH (2008) MetaSim—A Sequencing Simulator for Genomics and Metagenomics. PLoS ONE 3(10): e3373. doi:10.1371/journal.pone.0003373
| Run Unix # MetaSim | Run Web # |
| Version | MAJ | micca | ||
| 1.5.0 | 2017-02-27 | Download | Doc |
micca (MICrobial Community Analysis) is a software pipeline for the
processing of amplicon sequencing data, from raw sequences to OTU tables,
taxonomy classification and phylogenetic tree inference. The pipeline can be
applied to a range of highly conserved genes/spacers, such as 16S rRNA gene,
Internal Transcribed Spacer (ITS) and 28S rRNA.
Remarque
| Run Unix # micca [--version] [--help] | Run Web # |
| Version | MAJ | MOCAT | ||
| 1.1 | 2012-08-01 | Download | Doc |
MOCAT is a package for analyzing metagenomics datasets. Currently MOCAT supports Illumina single- and paired-end reads in raw FastQ format.
Remarque Jens Roat Kultima & Shinichi Sunagawa (Bork Group, EMBL)
| Run Unix # MOCAT.pl -sf|sample_file 'FILE' [Pipeline, Statistics, & Additional Options] | Run Web # |
| Version | MAJ | qiime | ||
| 1.9.1 | 2016-11-14 | Download | Doc |
QIIME (pronounced "chime") stands for Quantitative Insights Into Microbial Ecology. QIIME is an open source software package for comparison and analysis of microbial communities, primarily based on high-throughput amplicon sequencing data (such as SSU rRNA) generated on a variety of platforms, but also supporting analysis of other types of data (such as shotgun metagenomic data). QIIME takes users from their raw sequencing output through initial analyses such as OTU picking, taxonomic assignment, and construction of phylogenetic trees from representative sequences of OTUs, and through downstream statistical analysis, visualization, and production of publication-quality graphics. QIIME has been applied to single studies based on billions of sequences from thousands of samples.
Remarque
| Run Unix # qiime_env | Run Web # |
| Version | MAJ | SUPER-FOCUS | ||
| 0.26 | 2016-10-04 | Download | Doc |
SUPER-FOCUS, SUbsystems Profile by databasE Reduction using FOCUS, an agile
homology-based approach using a reduced SEED database to report the
subsystems present in metagenomic samples and profile their abundances. The
tool was tested with over 70 real metagenomes, and the results show that our
approach accurately predicts the subsystems present in microbial communities,
and it can be up to over 1,000 times faster than other tools.
Remarque
| Run Unix # | Run Web # |
