Parallel-META is a software toolkit which can perform rapid data mining among massive microbial community data for comparative taxonomical and functional analysis.
Based on parallel algorithms, Parallel-META can achieve a very high speed compare to traditional metagenomic analysis pipelines.
Parallel-META now supports 16S & 18S rRNA taxonomical analysis and KEGG based predictive functional analysis for microbial community samples, phylogenetic and functional comparison and feature selection.
Here we provide human oral microbial community sampless equenced by 454 Titanium in three different healthy conditions (“B” for healthy baseline, “I” for natural gingivitis and “E” for experimental gingivitis) produced by Huang, et al., 2014.
Dataset1, 150 samples in total, 3 healthy status;
Dataset2, 20 samples in total, 2 healthy status.
Now 3.2.1 Released (Apr 13, 2016)
3.2.1 (Apr 13, 2016) X86-64 (bin package / src package) X86 (bin package / src package) 3.2.0 (Jan 14, 2016) X86-64 (bin package / src package) X86 (bin package / src package) 3.1.0 (Dec 09, 2015) X86-64 (bin package / src package) X86 (bin package / src package) 3.0.1 ( Nov 03, 2015) X86-64 (bin package / src package) X86 (bin package / src package) 2.4.1 ( 08/20/2014 ) src package
1. Su X., Pan W., et al.,Parallel-META 2.0: Enhanced Metagenomic Data Analysis with Functional Annotation, High Performance Computing and Advanced Visualization, PLoS ONE, 2014.
2. Su X., et al. Parallel-META: Efficient Metagenomic Data Analysis Based on High-Performance Computation, BMC Systems Biology, 2012.