longread-UMI-pipeline

A collection of scripts for processing longread UMI data. Tested on Linux 3.10.0

Citation:
Karst, S. M., Ziels, R. M., Kirkegaard, R. H., & Albertsen, M. (2019). Enabling high-accuracy long-read amplicon sequences using unique molecular identifiers and Nanopore sequencing. bioRxiv, 645903. https://www.biorxiv.org/content/10.1101/645903v2

Installing the Easy Way -- via Conda

Requirements/Dependencies

Conda or Miniconda3 installed
usearch version 10 or higher

Clone from github

1. Go to desired installation directory, open a terminal and run:
   git clone https://github.com/ziels/longread-UMI-pipeline

2. Go to scripts directory:
   cd longread-UMI-pipeline/scripts

3. Modify dependencies.sh with path to usearch
   Change line export USEARCH=usearch_path to give your exact file path to the usearch executable file (instead of usearch_path).

Install conda environment

conda env create -f environment.yaml

1. Check that Conda env is installed
   conda info —-envs

Make sure you get something like:

# conda environments:
#
longread-UMI <path to conda envs>/longread-UMI

Note the installation path of the longread-UMI environment (for next steps)

2. Activate conda environment
   conda activate longread-UMI
   Or, depending on your conda version: source activate longread-UMI

Editing porechop adapters with custom primers

1. Find path of conda environments from command
   conda info —-envs

2. Check the porechop path works:
   ls < path to conda environments >/longread-UMI/lib/python3.6/site-packages/porechop

Make sure you see an adapters.py returned from the above command.

3. Back-up and replace adapters.py
mv <path_to_conda_environments>/longread-UMI/lib/python3.6/site-packages/porechop/adapters.py <path_to_conda_environments>/longread-UMI/lib/python3.6/site-packages/porechop/adapters_old.py

(From within longread-UMI-pipeline/scripts directory):
cp ./adapters.py <path_to_conda_environments>/longread-UMI/lib/python3.6/site-packages/porechop/adapters.py

Test longread-UMI-pipeline on test data:

Go to /path/to/longread-UMI-pipeline/test_data
Open a terminal in the directory and run
../longread_UMI_pipeline.sh -d test_reads.fq -s 10 -c 30 -t 1

Installing the Hard Way -- Manual installation

Requirements/Dependencies

Clone from github

1. Go to desired installation directory, open a terminal and run:
   git clone https://github.com/SorenKarst/longread-UMI-pipeline

Make bash scripts executable

1. Go to longread-UMI-pipeline directory, open a terminal and run:
   find . -name "*.sh" -exec chmod +x {} \;

Create symlink to run longread-UMI-pipeline and longread-UMI-mockanalysis from terminal

1. Create symlink in ~/bin by opening a terminal and run:
   mkdir -p ~/bin
ln -s /path/to/longread-UMI-pipeline/longread_UMI_pipeline.sh ~/bin/longread-UMI-pipeline
ln -s /path/to/longread-UMI-pipeline/longread_UMI_mockanalysis.sh ~/bin/longread-UMI-mockanalysis

Change paths to dependencies

1. Open /path/to/longread-UMI-pipeline/scripts/dependencies.sh in a texteditor.
2. Change all paths under "Program paths" to reflect installation paths on your system.
3. If unsure of the paths try to type which <function> in the terminal. I.e. which racon.
4. Install any missing dependencies.

Customize porechop adaptors.py to be able to detect custom primers

1. We recommend to make a seperate installation of porechop to use with the longread-UMI-pipeline.
2. Go to path/to/porechop/porechop/
3. Backup current adapters.py.
4. Replace current adapters.py with path/to/longread-UMI-pipeline/scripts/adapters.py.

Test scripts

1. Open a terminal anywhere and run:
   longread-UMI-pipeline -h or /path/to/longread-UMI-pipeline -h
2. Test longread-UMI-pipeline on test data:
   Go to /path/to/longread-UMI-pipeline/test_data
   Open a terminal in the directory and run longread-UMI-pipeline -d test_reads.fq -s 10 -c 30 -t 1

Run pipeline on Zymo mock data

1. Create a working directory, open a terminal, download the Zymo mock fastq data and decompress:
   wget ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR333/003/ERR3336963/ERR3336963_1.fastq.gz; gunzip -c ERR3336963_1.fastq.gz > reads.fq
2. Open a terminal in the directory and run:
   longread-UMI-pipeline -d reads.fq -s 1000000 -c 30 -t <Number-of-threads>
3. Open a terminal in the directory and run:
   longread-UMI-mockanalysis <Number-of-threads>