transposonmapper 1.1.5

A libray for processing sequencing data for SAturated Transposon Analysis in Yeast (SATAY)

SATAY and Transposonmapper

This workflow is created for processing sequencing data for SAturated Transposon Analysis in Yeast (SATAY) for Saccharomyces Cerevisiae. It performs the steps from raw sequencing data until the transposon mapping that outputs files containing all insertion sites combined with the number of reads.

For more information regarding SATAY, see the satay user website created by the Kornmann-lab. For more extensive documentation, see our JupyterBook.

The workflow requires input sequencing data in fastq format. It can perform the following tasks:

• sequence trimming

• quality checking raw and trimmed fastq files

• sequence alignment with reference genome (S288C Cerevisiae genome)

• quality checking bam files, indexing and sorting

• transposon mapping

The output files indicate the location of transposon insertions and the number of reads at those locations. This is presented in both .bed and .wig format. Also a list of genes is generated where the number and distribution of insertions and reads is presented per (essential) gene.

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Documentation for users

PyPI package

For users that only require post processing analysis of the data (the bam file was already analyzed), do use the default installation. For example pysam won’t be installed, hence Linux is not required.

pip install transposonmapper

For users that require the whole processing pipeline, do use:

pip install transposonmapper[linux]

For more extensive documentation, see our JupyterBook.

SATAY pipeline

We provide two methods to run the SATAY pipeline, either with a Docker container (recommended) or a Linux system. The workflow relies on the following libraries:

• FASTQC v0.11.9 or later

• BBMap v38.87 or later

• Trimmomatic v0.39 or later

• BWA v0.7.17 or later

• SAMTools v1.10 or later

• BCFTools v1.10.2-3 or later

• Sambamba v0.7.1 or later

• Transposonmapper

These libraries are called as a processing pipeline by the script satay.sh, which generates a GUI.

Preprocessing steps

Before inputting the data into the satay pipeline, it is necessary to preprocess the data that comes from the sequencing company.

The pipeline does not process each digestion separately and therefore any pre-processing and trimming of the restriction sites should be done prior to running the pipeline.

What we do if the sequencing data is paired end:

If the data is paired end, only one of the pairs will map to the transposon insertion site (the end that has been sequenced from the sequencing primer), while the other end will map back to a location arbitrarily far upstream or downstream of the insertion site (depends on where the restriction site is).

Preprocessing steps prior to use the satay pipeline:

• Convert the data to single end by:

  • Extracting the forward reads, which are the reads that contain the sequencing primer, as it is (harsh filtering) or allowing some mismatches in the sequencing primer, due to likely sequencing errors (gentle filtering).

• Remove the sequence downstream the first restriction site for NiaIII and DpnII to avoid having chimeras sequences in our data, that have poor alignment.

  • Discard reads bellow 50bp after trimming of the restriction site to ensure a decent confidence alignment score for that read.

Docker

For a full installation and user guide for Docker containers, see our documentation.

The Docker image is hosted at leilaicruz/satay.

Prerequisites:

• Windows, macOS, Linux

• Docker

• Xserver (for displaying the GUI)

To build the image locally in your computer, from DockerHub:

• create an account in DockerHub

• Pull the image

docker pull leilaicruz/satay:latest

• Verify the image is in your computer

docker images

• Move to where you have the Dockerfile and build the image

docker build . -t leilaicruz/satay:latest

• Move to the location where you have the data you would like to mount to the container, to use $(pwd) in the command bellow (simplest option), otherwise indicate the absolute path from your computer you would like to be loaded.

To run the docker container, use the commands for your Operating System:

# For Windows (and WSL):
docker run --rm -it -e DISPLAY=host.docker.internal:0 -v /$(pwd):/data leilaicruz/satay:latest

# For macOS
docker run --rm -it -e DISPLAY=docker.for.mac.host.internal:0 -v $(pwd):/data leilaicruz/satay

# For Linux
docker run --rm -it --net=host -e DISPLAY=:0 -v $(pwd):/data leilaicruz/satay

• The flag -e enables viewing of the GUI outside the container via the Xserver

• The flag -v mounts the current directory (pwd) on the host system to the data/ folder inside the container

• Troubleshooting

If an error regarding the connection pops up:

Gtk-WARNING **: cannot open display: :0

There is a solution in Linux is typing the following command in the terminal : xhost +

Linux system

Prerequisites:

• Anaconda

• Python 3.7, 3.8

We recommend installing all dependencies in a conda environment:

git clone https://github.com/SATAY-LL/Transposonmapper.git satay
cd satay
conda env create --file conda/environment-linux.yml
conda activate satay-linux

To start the GUI, simply run

bash satay.sh

Documentation for developers

Installation

To install transposonmapper, do:

git clone https://github.com/SATAY-LL/Transposonmapper.git
cd transposonmapper
conda env create --file conda/environment-dev.yml
conda activate satay-dev
pip install -e .[dev]

Run tests (including coverage) with:

pytest

Docker image

For more information go to our [Jupyter Book](https://satay-ll.github.io/Transposonmapper/03-docker-doc/03-Docker-Developers.html)

Contributing

If you want to contribute to the development of transposonmapper and the SATAY pipeline, have a look at the contribution guidelines.

Contributors

This software is part of the research effort of the LaanLab, Department of BioNanoScience, Delft University of Technology

• Leila Iñigo de la Cruz

• Gregory van Beek

• Maurits Kok

License

Copyright (c) 2020, Technische Universiteit Delft

Licensed under the Apache License, Version 2.0 (the “License”). The 2.0 version of the Apache License, approved by the ASF in 2004, helps us achieve our goal of providing reliable and long-lived software products through collaborative open source software development.

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an “AS IS” BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.