Package: massdash
MassDashis a powerful platform designed for researchers and analysts in the field of mass spectrometry. By providing a centralized web-based dashboard, MassDash facilitates data analysis and experiment design by enabling users to visualize chromatograms, test algorithms, and optimize parameters. This tool offers a flexible environment for mass spectrometry research, with notable specailty in handling Data-Independent Acquisition (DIA) data.InstallationRecommended: Install the latest stable version of MassDash from the Python Package Index (PyPI):pipinstallmassdash--upgradeor if you use Anaconda for package and environment management, then you can install from bioconda:condainstallbioconda::massdashInstalling from sourceClone the repository:gitclonehttps://github.com/Roestlab/massdash.gitChange intomassdashdirectory:cdmassdashInstallmassdashin editable mode:pipinstall-e.Quick startLaunch MassDash by typing the following command in your terminal:massdashguiFeaturesMassDash empowers researchers to streamline mass spectrometry workflows, experiment with data analysis algorithms, and optimize parameters to enhance research accuracy and efficiency. Below are some of MassDash's notable features:Chromatogram visualization: Easily view and analyze chromatograms for an in-depth examination of mass spectrometry data.Algorithm testing: Develop and fine-tune custom algorithms by interfacing with MassDash's various data analysis algorithms and workflows.Parameter optimization: Ensure optimal results for your experiment by optimizing parameters for data analysis workflows, such asOpenSwathWorkflow.User-friendly dashboard: MassDash's dashboard is designed with users in mind, facilitating research productivity in both beginners and experts in the field.Data exploration: Explore mass spectrometry data with our suite of tools and gain insights to make informed research decisions.Customization: Flexibly tailor data analysis parameters and results for specific research needs.Rapid prototyping: Save time and resource when developing mass spectrometry workflows by quickly prototyping and testing research ideas.Data integration: Seamlessly import, process, and export data to facilitate data sharing and collaboration.Launching MassDash from a remote machineSSH into a remote machine and installmassdash; it's highly recommended to installmassdashin a Python virtual environment to contain project-specific dependencies:sshyour_user_name@remote_ip_addresspipinstallmassdashLaunch MassDash:massdashguiTwo URLs with an IP address and port number will appear in the terminal after launching MassDash; for example:Network URL: http://192.168.142.176:8501
  External URL: http://142.150.84.40:8501Enter the following command in a local machine's terminal, replacing "----" with the URL port number (e.g., 8501):ssh-fNL----:localhost:----your_user_name@remote_ip_addressYou can now view MassDash on the local machine's browser by clicking on either of the provided URLs.DockerMassDash is also available on Docker.Pull the latest stable version of MassDash from DockerHub:dockerpullsingjust/massdash:latestSpin up the MassDash Docker container:dockerrun-p8501:8501singjust/massdash:latestNote:The MassDash Docker image binds to port 8501 when running MassDash locally.ContributeIssues TrackerSource CodeSupportIf you are having issues or would like to propose a new feature, please use theissues tracker.LicenseThis project is licensed under the BSD 3-Clause license.CitationSing, J. C., Charkow, J., AlHigaylan, M., Horecka, I., Xu, L., & Roest, H. L. (2024). MassDash: A Web-based Dashboard for Targeted Mass Spectrometry Visualization (p. 2024.01.15.575772). bioRxiv.https://doi.org/10.1101/2024.01.15.575772