Parallel-Meta Suite

  • Introduction
  • Parallel-Meta Suite is a comprehensive and full-automatic computational toolkit for rapid data mining among metagenomic datasets. Both metagenomic shotgun sequences and 16S/18S/ITS rRNA amplicon sequences are accepted. Based on parallel algorithms and optimizations, Parallel-Meta Suite can achieve a very high speed compare to traditional microbiome analysis pipelines. Now the Parallel-Meta Suite version 3.7.2 is available at http://bioinfo.single-cell.cn/parallel-meta.html.

  • Download
  • The following functions have been updated in the version 3.7.2 of Parallel-Meta Suite.

    • Add new databases, including GreenGenes 2 and RefSeq
    • Add PM-profiler as a new taxonomy profiler

    We strongly recommend all users to install/update the latest version.

    3.7.3 (July 3, 2024)

    Linux X86-64 (src package)
    Mac (Intel/M2/M3) (src package)

    You can also get the lastest release from Parallel-Meta Suite GitHub respository.

    • System requirement
    • Mac OS X needs to install the compiler that supports OpenMP by
      brew install gcc
    • Quick installation
    • Type the following commands in the directory that contains the package for quick installation:
      tar -xzvf parallel-meta-3.7-src.tar.gz #Extract the package
      cd parallel-meta#Go to the package directory
      source install.sh#Automatic installation
    • The example dataset could be found at “example” folder. Check the “example/Readme” for details about the demo run.
  • Tutorial and Demo dataset
  • Here we provide a demo dataset with 20 environment microbiome samples in five different environment(feces, tongue, palm, soil, marine). See the tutorial and"Readme" in the dataset package for details.

    Tutorial of Parallel-Meta

    Sample Dataset and Sample output (by 3.7.2, GreenGenes 13-8 97% level, Vsearch)

  • Publications
  • 1. Chen., et al., Parallel‐Meta Suite: Interactive and rapid microbiome data analysis on multiple platforms, iMeta, 2022.

    2. Jing., et al., Parallel-META 3: Comprehensive taxonomical and functional analysis platform for efficient comparison of microbial communities, Scientific Reports, 2017.

    3. 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.

    4. Su X., et al. Parallel-META: Efficient Metagenomic Data Analysis Based on High-Performance Computation, BMC Systems Biology, 2012.

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