- html reporting
- automatic parallelization
- automatic resume function
- extensive quality control
- interactive principal component analysis
Pre-requisites
Hydra requires Java 1.6+. All other tools are wrapped in a Conda environment, see below.
1. Get Conda
conda is available as part of the miniconda package.
Note
If you're using a module system such as on the shared computing cluster (SCC) at Boston University you can just load a preinstalled version:
module purge
module load anaconda/2.2.0
2. Create Dev Environment
Use conda to install a basic developement environment:
conda create \ -p ./dev_env \ -c https://conda.anaconda.org/montilab \ --yes \ hydra
This will create a `./dev_env folder that stores all the files needed to run the pipeline. For more details, please refer to the Developer's Guide. (LINK)
3. Install all necessary R packages Activate the environment so you have access to the R version that the pipeline uses:
source activate ./dev_env
Start R:
R
Within R install all necessary packages:
source("http://bioconductor.org/biocLite.R") biocLite(c("Biobase",'edgeR'),ask=F) install.packages(c("devtools","knitr", "yaml", "rjson","codetools"), repos='http://cran.us.r-project.org') devtools::install_github("nachocab/clickme")
Activate the environment (follow the instructions provided by conda following the environment's creation):
source activate ./dev_env
Then you can run the pipeline, while providing your parameter file.
Example:
hydra-rnaseq -p param.txt
A detailed description of the parameter file is provided here and an example is located here here .
A detailed user documentation is provided here. For advanced users that are contributing to the development such as adding additional modules a documentation is provided here