NB! For the latest version of this pipeline go to: AfshinLab/BLR
Content:
Activate your Conda environment.
conda activate blr
Choose a name for the analysis. It will be output_folder in this example. Create
the analysis directory.
blr init --reads1=path/to/sample.R1.fastq.gz path/to/output_folder
Note that BLR expects paired-end reads. However, only the path to the R1 file needs to be provided. The R2 file will be found automatically.
To use the other blr commands, make sure you working directory is your newly created analysis folder.
cd path/to/output_folder
Then, you may need to edit the configuration file blr.yaml, in
particular to enter the path to your reference genome.
blr set --genome_reference=path/to/GRCh38.fasta
To see what other configurations can be altered, read the documentation in
the blr.yaml file.
Change working directory to your analysis folder
cd path/to/output_folder
The pipeline automatically runs all steps.
blr run
For more options, see the documentation.
blr run -h
- Install miniconda
- Enable the bioconda channel
You could also try copy-pasting the following to your terminal. This will download miniconda,
install it to you $HOME folder and enable the bioconda channel.
if [[ $OSTYPE = "linux-gnu" ]]; then
wget http://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh
elif [[ $OSTYPE = "darwin"* ]]; then
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh -O miniconda.sh
fi
bash miniconda.sh -b -p $HOME/miniconda
source $HOME/miniconda/etc/profile.d/conda.sh
conda config --add channels bioconda
Clone the git repository.
git clone https://github.com/FrickTobias/BLR.git
Create & activate a new Conda environment, in which all dependencies will be installed.
conda env create -n blr -f environment.yml
conda activate blr
Install blr into the environment in "editable install" mode.
pip install -e .
This will install blr in such a way that you can still modify the source code and get any changes immediately without re-installing.
To enable DeepVariant, install it separately to your environment.
conda activate blr
conda install deepvariant
This will enable the variant_caller: deepvariant option in the analysis config file.
Change working directory to your blr git folder and update.
cd path/to/BLR
git pull
To run the analysis described in High throughput barcoding method for genome-scale phasing, look at the stable branch for this git repository.
That version of BLR Analysis is also available at OMICtools.