:: DESCRIPTION
SFA-SPA is a suffix array based short peptide assembler for metagenomic data
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
SFA-SPA: a suffix array based short peptide assembler for metagenomic data.
Yang Y, Zhong C, Yooseph S.
Bioinformatics. 2015 Jan 30. pii: btv052.
:: DESCRIPTION
REAGO is an assembly tool for 16S ribosomal RNA recovery from metagenomic data
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Reconstructing 16S rRNA genes in metagenomic data.
Yuan C, Lei J, Cole J, Sun Y.
Bioinformatics. 2015 Jun 15;31(12):i35-i43. doi: 10.1093/bioinformatics/btv231.
:: DESCRIPTION
myPhyloDB is an open-source software package aimed at developing a user-friendly web-interface for accessing and analyzing all of your laboratory’s microbial ecology data.
::DEVELOPER
: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
myPhyloDB: a local web server for the storage and analysis of metagenomic data.
Manter DK, Korsa M, Tebbe C, Delgado JA.
Database (Oxford). 2016 Mar 28;2016. pii: baw037. doi: 10.1093/database/baw037.
:: DESCRIPTION
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.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation:
SUPER-FOCUS: A tool for agile functional analysis of shotgun metagenomic data.
Silva GG, Green KT, Dutilh BE, Edwards RA.
Bioinformatics. 2015 Oct 9. pii: btv584.
:: DESCRIPTION
BURRITO is a web-based tool for interactive exploration of metagenomic datasets, linking taxonomic and functional microbiome profiles
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Front Microbiol. 2018 Mar 1;9:365. doi: 10.3389/fmicb.2018.00365. eCollection 2018.
BURRITO: An Interactive Multi-Omic Tool for Visualizing Taxa-Function Relationships in Microbiome Data.
McNally CP, Eng A, Noecker C, Gagne-Maynard WC, Borenstein E.
:: DESCRIPTION
EMPANADA is a tool for evidence-based, non-uniform, and sample-specific assignment of gene families to pathways in metagenomic data.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
:: DESCRIPTION
Amordad is a database engine for comparing metagenomic data at massive scale. It first obtains the sequence signature of metagenomes and organizes them as points in high dimensional space.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Bioinformatics. 2014 Jun 27. pii: btu405. [Epub ahead of print]
The Amordad database engine for metagenomics.
Behnam E, Smith AD.
:: DESCRIPTION
MicrobeGPS is a bioinformatics tool for the analysis of metagenomic sequencing data. The goal is to profile the composition of metagenomic communities as accurately as possible and present the results to the user in a convenient manner.
::DEVELOPER
MicrobeGPS Team
:: SCREENSHOTS
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Metagenomic profiling of known and unknown microbes with microbeGPS.
Lindner MS, Renard BY.
PLoS One. 2015 Feb 2;10(2):e0117711. doi: 10.1371/journal.pone.0117711.
:: DESCRIPTION
growthpred predicts the minimum generation time for a bacterial or archaeal organism based on its codon usage bias intensity (CUB). The CUB index is calculated given two input sets of sequences: 1) highly expressed genes 2) other genes. The application runs 1000 bootstraps and outputs the average and the standard deviation of the predictions.
::DEVELOPER
Microbial evolutionary genomics , Institut Pasteur
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation:
Vieira-Silva S, Rocha EPC, 2010
The Systemic Imprint of Growth and Its Uses in Ecological (Meta)Genomics.
PLoS Genet 6(1): e1000808. doi:10.1371/journal.pgen.1000808
:: DESCRIPTION
Metastats, employs the false discovery rate to improve specificity in high-complexity environments, and separately handles sparsely-sampled features using Fisher’s exact test. Under a variety of simulations, we show that Metastats performs well compared to previously used methods, and significantly outperforms other methods for features with sparse counts. We demonstrate the utility of our method on several datasets including a 16S rRNA survey of obese and lean human gut microbiomes, COG functional profiles of infant and mature gut microbiomes, and bacterial and viral metabolic subsystem data inferred from random sequencing of 85 metagenomes. The application of our method to the obesity dataset reveals differences between obese and lean subjects not reported in the original study. For the COG and subsystem datasets, we provide the first statistically rigorous assessment of the differences between these populations.
::DEVELOPER
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation:
PLoS Comput Biol. 2009 Apr;5(4):e1000352. Epub 2009 Apr 10.
Statistical methods for detecting differentially abundant features in clinical metagenomic samples.
White JR, Nagarajan N, Pop M.
