The goal of BiomassWorkflow is to streamline data analysis and removing the potential for errors in the process. The package is most useful for generating microbial density data and comparing microbial density between various groups. There are also a couple of helper functions included and other scripts that help with moving samples through the processing pipeline.
The full installation of this package is a bit complicated because it requires various dependencies in order to work fully. (I'm working on slimming this down)
First, you will need to install a few things in R in order to get this package to work. Simply follow the following commands:
# Install devtools, a package that helps install other packages from GitHub/Bitbucket install.packages("devtools") # Install this package ("BiomassWorkflow") from Bitbucket (or GitHub via devtools::install_github('econtijoch/Biomass-Workflow') ) devtools::install_bitbucket("econtijoch/biomass-workflow") # Source BiocLite and install rhdf5 - a package necessary for being able to read hdf5-formatted .biom tables source("https://bioconductor.org/biocLite.R") biocLite("rhdf5") # Update to the development verison (0.4.0) of the biom R package that can accept hdf5 .biom files devtools::install_github('joey711/biom')
There is a very strong chance that this alone will not be enough. You will also need to set up java to play nicely with R and this package. To do that, you'll need to go to terminal and type:
sudo R CMD javareconf
This will prompt you for your password in order to execute.
Then, back in R, you will need to re-install the rJava library:
That should be all you need to do to get the package working. If for some reason that is not enough, you may need to install the latest version of Java, and then go through the last few steps again.
I am working on updating the documentation for the tutorial. So far, there is an introductory tutorial that will get you through generating a measurement of microbial density here. Upcoming is a tutorial to walk through prepping samples for sequencing.
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