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environment.md

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RASE computational environment

The easiest way how to setup a computational environment for RASE is using Bioconda.

Dependencies

Setting up an environment

Using a separate BioConda environment

We recommend to create a separate software environment (here called rase):

conda create -n raseenv \
	prophyle ete3 pysam snakemake-minimal samtools parallel r-optparse pandas seqtk

The environment can then be activated by

source activate raseenv

To avoid failures on very long reads, we recommend upgrading ProPhyle to a corrected version:

source activate raseenv
pip install --upgrade git+git://github.com/prophyle/prophyle.git@b55e026

Alternative ways of installation

All the dependencies can also be installed without BioConda.

Many of these packages are distributed using standard package systems such as APT.

apt-get install build-essential python3 zlib1g-dev r-base r-cran-optparse ghostscript

All the Python packages (ProPhyle, PySAM, ETE 3, and Snakemake) can be installed using PIP:

pip3 install prophyle pysam ete3 snakemake

Known issues

libR.dylib Reason: image not found

At some systems, the R package distributed by Bioconda might not be properly built and would display messages such as

dyld: Library not loaded: @rpath/libintl.9.dylib
  Referenced from: /Users/user/miniconda/envs/rase/lib/R/lib/libR.dylib
  Reason: image not found
Abort trap: 6

The solution is then to create the raseenv environment without r-optparse, and to install R and the OptParse package manually.

ETE: cannot connect to X server

ETE 3 library, which is used for tree plotting, internally depends on QT and requires using an X-Server. This becomes problematic especially on virtual machines. For instance, on Ubuntu-based machines this can be solved by installing several additional packages:

apt-get install xvfb libqt4-dev libgl1-mesa-dev libglu1-mesa-dev xauth xfonts-base

and then prepending the following string to commands for building the database.

xvfb-run --server-args="-screen 0 1024x768x24 -noreset" \