raytonghk / genepiper

GenePiper
GNU Affero General Public License v3.0
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GenePiper

GenePiper is a standalone R shiny application for NGS data mining. It provides over 20 different analysis methods with user-friendly GUI. Recently, 6 main categories of analytic modules (Diversity, Descriptive, Oridination, Correlation, Clustering and Non-parametric test) are included.

Installation


Software requirements:

Installation:

  1. Download the Vagrantfile: press ALT (or option key in Apple keyboard) + click "Raw" at the top right corner
  2. Create a working directory and copy the Vagrantfile into it.
  3. If the Vagrantfile contains any extension, e.g. .txt, remove it.
  4. Run vagrant up in the working directory in terminal (Linux / Mac) or command prompt (Windows).
  5. After installation, use any web browser (such as Chrome, Firefox, Safari) to host machine: type in the address bar http://localhost:4002.

Installation involves building a virtual environment, installing the operation system (linux), all the essential tools and packages, R Shiny server setup and configuration of the environment. This one-time process may take over 30 minutes.

To update:

We are actively updating and improving GenePiper, users are advised to update the package time to time for new patches and newly added functions. To update GenePiper, click on the "Update Genepiper" button when you first launch the package in your browser.

Sample data:

Sample data GlobalPatterns from phyloseq package is provided in RDS format gp.rds in the sampleData folder. Individual table files had been extracted as sample data:

Reference:

Caporaso, J. G., et al. (2011). Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. PNAS, 108, 4516-4522. PMCID: PMC3063599

Biom sample file rich_dense_otu_table.biom is also provided.

Tutorials:

For detailed walkthrough of each module, please refer to our Wiki page.

Future updates:

Citation:

Please cite GenePiper as follows: "Tong WM, Chan Y. 2020. GenePiper: a graphical user interface tool for microbiome sequence data mining. Microbiol Resour Announc 9:e01195-19. https://doi.org/10.1128/MRA.01195-19."