Pytheas has been fully tested on Windows 10, Linux (Ubuntu 20.04+) and macOS (10.14+, note that you need to use pythonw when launching the scripts on macOS). In the current release, there are two supported versions, one with a graphical interface (GUI) and one exclusively command line based (CL). The GUI version is the preferred one, but in case the user experiences issues while using it, the CL version is a good alternative albeit less user-friendly. For the purposes of inputs and outputs the scripts of the two versions are identical. Both versions require to call the component of the Pytheas workflow via command line, but the GUI version offers to the user a graphical interface to select the parameters and run the analysis. A third option is to run Pytheas through Docker, using the provided Dockerfile to build the image. Several instances of files and libraries needed for the execution of other scripts (either already present or created while running Pytheas) are packaged together in the same directory, please be careful if moving the scripts from their original position as it may break some dependencies. It is therefore suggested to run the scripts in their provided directories and transfer around only the output files generated.

From the GitHub repository Pytheas can be downloaded either selecting the green “Code” button and choosing “Download ZIP” or cloning locally the git repository. The first option downloads a compressed directory with all the files, including the two GUI version and CL version main working directories. To clone the git repository, install git (Windows instructions), then open a shell prompt (in Windows under Start > Command Prompt) and navigate into the desired directory for cloning Pytheas repository. Then, within this directory run git clone https://github.com/ldascenzo/pytheas.git This will create a pytheas directory at the chosen location, with all the files needed to run Pytheas.

Download the latest Anaconda version based on the Windows version in usage (by April 2021 it is Python 3.8 Windows 64-bit Graphical Installer). Install Anaconda leaving the standard options selected.

Open an Anaconda Powershell Prompt (Start menu -> Anaconda Powershell Prompt). Within the prompt install some Python packages needed for Pytheas execution.

conda create -n pytheas-env python=3.10 -y
conda activate pytheas-env
conda install -y numpy==1.23.1 pandas==1.4.1 matplotlib==3.5.0
conda install -y -c conda-forge gooey biopython
conda install -y -c bioconda pyteomics
conda install -y -c anaconda openpyxl

Install the latest Python 3 version

$ sudo apt-get update
$ sudo apt-get install python3

Install pip, Python package manager to easily download, update and maintain all the libraries

$ sudo apt install -y python3-pip

Install some additional libraries that will be needed later, confirming with Y when needed during the installation.

$ sudo apt-get install git curl libsdl2-mixer-2.0-0 libsdl2-image-2.0-0 libsdl2-2.0-0

Install the wxPython package, which will be used for the GUI version.

$ wget  -P ~ "https://extras.wxpython.org/wxPython4/extras/linux/gtk3/ubuntu-20.04/wxPython-4.1.0-cp38-cp38-linux_x86_64.whl"
$ pip3 install ~/wxPython-4.1.0-cp38-cp38-linux_x86_64.whl

Navigate to the local pytheas directory, then install all the requirements needed from the file requirements.txt. In case of problems with any of those, please refer to the respective documentations.

$ pip3 install -r requirements.txt

The Anaconda installation described for the Windows version is the recommended way of installing Pytheas dependencies. On top of the Windows instructions, the requirements to run the GUI version are installing python.app with

conda install -c anaconda python.app

And calling the scripts using pythonw

Install Docker Desktop Open a Command Prompt (from the Start menu) and pull the Pytheas Docker image

docker pull ldascenzo/pytheas:latest

Follow the installation instructions for Docker Open a Terminal prompt to pull the Pytheas Docker image

docker pull ldascenzo/pytheas:latest

Using an Anaconda Powershell Prompt, navigate to the local pytheas directory. If for example the directory is in C:\Users\MainUser\pytheas the command will be cd C:\Users\MainUser\pytheas

Navigate inside the directory of the chosen version (by default the GUI version) and run the scripts inside the respective sub-directories by using python pytheas_<script_name>.py

Select the options and parameters using the provided graphical interface. Refer to the Fig.1 of the main text and to the manual for more details on the order of the workflow and the usage/output of the single scripts.

Navigate within the Pytheas version directory (GUI or CL) and launch the scripts with python3 pytheas_<script_name>.py

Note that python3 instead of python may not be necessary if the default Python installation is set to be the 3. Refer to the Fig.1 of the main text and to the manual for more details on the order of the workflow and the usage/output of the single scripts.

Navigate within the Pytheas version directory (GUI or CL) and launch the scripts with pythonw pytheas_<script_name>.py

Open a Bash shell within the container docker run -it ldascenzo/pytheas /bin/bash

Navigate within the main Pytheas directory, in the command line version # cd pytheas/CL_version

From there run Pytheas scripts following the normal instructions for the CL version To transfer files between the Docker container and the host, use the following docker cp <container name>:/file/path/within/container /host/path/target

After the installation of Pytheas and all the dependencies, the training set output files can be reproduced by running the following steps. All three steps of this simple demo can be run in a few minutes on an average laptop or desktop computer.

Within the GUI_version/in_silico_digestion directory, the digest file can be obtained by running python pytheas_insilico_digestion.py And changing the standard options for (all files are found within the Training_set directory):

• RNA_sequences = calibration_set_sequences.fasta
• Enzyme = None
• Nucleotides_light = nts_light.xlsx
• decoys = selected
• list_of_known_RNA_modifications = modfile_calibration_set.txt
• RNA_5end_chemistry = OH
• RNA_3end_chemistry = P

Within the GUI_version/matching_scoring directory, the matching and scoring files can be obtained by running python pytheas_matching_scoring.py And changing the standard options for (all files except the digest are found within the Training_set directory):

• Theoretical_digest = digest file obtained from the previous step
• MS_data = calibration_set.mgf
• isotopic_species = light

Within the GUI_version/final_report, the final_report can be obtained by running python pytheas_final_report.py Using the matching file obtained in the previous step as Match_output