Instalation¶

Dependencies¶

There is number of packages that the pipeline requires.

CONTRAfold¶

Download and install CONTRAfold. It might be that you experience an error when compiling CONTRAfold. Something like this:

In file included from LBFGS.hpp:52:0,
                 from InnerOptimizationWrapper.hpp:12,
                 from OptimizationWrapper.hpp:12,
                 from Contrafold.cpp:16:
LBFGS.ipp: In instantiation of ‘Real LBFGS<Real>::Minimize(std::vector<T>&) [with Real = double]’:
OptimizationWrapper.ipp:260:9:   required from ‘void OptimizationWrapper<RealT>::LearnHyperparameters(std::vector<int>, std::vector<T>&) [with RealT = double]’
Contrafold.cpp:451:9:   required from ‘void RunTrainingMode(const Options&, const std::vector<FileDescription>&) [with RealT = double]’
Contrafold.cpp:68:54:   required from here
LBFGS.ipp:112:105: error: ‘DoLineSearch’ was not declared in this scope, and no declarations were found by argument-dependent lookup at the point of instantiation [-fpermissive]
LBFGS.ipp:112:105: note: declarations in dependent base ‘LineSearch<double>’ are not found by unqualified lookup
LBFGS.ipp:112:105: note: use ‘this->DoLineSearch’ instead
make: *** [Contrafold.o] Error 1

To fix it:

add -fpermissive flag to CSXXFLAGS in Makefile:

CXXFLAGS = -O3 -DNDEBUG -W -pipe -Wundef -Winline --param large-function-growth=100000 -Wall -fpermissive

instead of
CXXFLAGS = -O3 -DNDEBUG -W -pipe -Wundef -Winline --param large-function-growth=100000 -Wall

add in Utilities.hpp:

#include <limits.h>

We have tested our pipeline with version 2.02.

PLEXY¶

Please refer to PLEXY website for detailed installation instructions. As mentioned on the website be sure to have the latest version of RNAPLEX installed.

Jobber¶

Download and setup Jobber python library for workflow managment.

pip install Jobber

After installation start the Jobber daemon:

$ nohup jobber_server > jobber.log 2>&1 &

Note

If you installed Jobber as user you might not have an access to the jobber_server. By default the binary location is $HOME/.local/bin and you have to export it in bash:

$ export PATH="$HOME/.local/bin:$PATH"

or add this statement to .bashrc file.

jobber_server produces ~/.jobber/jobber.pid file that indicates whether the Jobber is already running. If the file exists one cannot start new instance of the jobber_server. This file is not clean when jobber_server is killed - only when it was stopped with stop command. Thus, after some crash one have to remove this file in order to start jobber_server again.

This will automatically create a ~/.jobber and ~/jobber/log directories and it will put there config.py and executers.py files. Look at them and adjust according to your needs.

This should create a jobber.sqlite file next to config.py where jobs will be stored (all in ~/.jobber). Now you can create pipelines that will be managed with a python script.

To stop the jobber daemon, run following command:

$ jobber_server -stop

You can watch and control your jobs and pipelines present in the database using simple we interface. To launch it type:

$ jobber_web

or

$ jobber_web --ip Your.IP.addres --port YourPort

Note

If you would like to run snoRNAHybridSearch pipeline locally without DRMAA change executer in config.py file from “drmaa” to “local”

BEDTools¶

Please refer to BEDTools website for detailed installation instructions. We have tested our pipeline with version 2.25.0.

ViennaRNA package¶

Please refer to ViennaRNA website for detailed installation instructions. We have tested our pipeline with version 2.1.8.

SAM Tools¶

Please refer to SAM Tools website for detailed installation instructions. We have tested our pipeline with version 1.2.

Bowtie 2¶

Please refer to Bowtie 2 website for detailed installation instructions. We have tested our pipeline with version 2.2.6.

Python¶

The pipeline works with Python 2.7.

Install required python modules:

Jobber (see upper paragraph)
drmaa (if you are going to submit it to the cluster)
statsmodels==0.6.1
pandas==0.18.0
biopython==1.66
numpy==1.10.4
scipy==0.17.0
swalign==0.3.3
configobj==5.0.6
HTSeq==0.6.1
MetaProfile==0.1.0
bx-python==0.7.3
HTSeq==0.6.1
Jinja2==2.8
matplotlib==1.5.3
pysam==0.9.1.4
patsy==0.4.1
seaborn==0.7.1
pybedtools==0.7.8
interval==1.0.0

Almost all python dependencies are in the requirements file so one can run:

$ pip install -r requirements.txt

However, ushuffle has to be installed manually (one can use this repo). The versions of the packages are the ones we have tested our pipeline on. One can use newer/older versions.

For documentation build and not necessary for run (and not included in the requirements.txt):

sphinx
sphinx-argparse
sphinx_rtd_theme

Download¶

The pipeline code is available as a git repository on GitHub or on our website:

git clone https://github.com/guma44/snoRNAHybridSearchPipeline.git

OR

wget http://www.clipz.unibas.ch/snoRNAchimeras/snoRNAHybridSearchPipeline.tar.gz

In order to run the example and to run pipeline it is neccessary to provide number of additional files including genome, annotations and snoRNA sequences. Preprepared files for GRCh37 can be downloaded from our website. If you would like to prepare your own data it is recomended to look at these files, too:

wget http://www.clipz.unibas.ch/snoRNAchimeras/snoRNAHybridSearchData.tar.gz

You can also download whole package including additional data from our website:

wget http://www.clipz.unibas.ch/snoRNAchimeras/snoRNAHybridSearch.tar.gz