GitHub Repository
Health-Universe/lesSDRF
Status
Ready
Created On
Updated On
Spending less time on SDRF creates more time for amazing research! By providing metadata in a machine-readable format, other researchers can access your data more easily and you maximize its impact. The Sample and Data Relationship Format (SDRF) is the HUPO-PSI recognized metadata format within proteomics. lesSDRF will streamline this annotation process for you. This tool is developed by the CompOmics group and published in Nature Communications.

More details

Use Cases Limitations Evidence Owner's Insight

The lesSDRF (Less time on Sample and Data Relationship Format) tool simplifies the annotation process for researchers working with proteomic data. Developed by the CompOmics group and published in Nature Communications, this tool streamlines the creation of metadata in a machine-readable format, maximizing the accessibility and impact of your data. The tool provides a user-friendly interface where researchers can select a species-specific default SDRF file matching their study and input raw file names. Through a series of steps in the sidebar, users can upload local metadata files, provide information on sample labels, and fill in required and additional columns for a valid SDRF. Additionally, users can download intermediate SDRF files at any point for flexibility in the annotation process. With lesSDRF, researchers can spend less time on metadata annotation and more time on groundbreaking research.

See owner's GitHub repository for more information: https://github.com/compomics/lesSDRF.

This app is based on the paper:

Claeys, T., Van Den Bossche, T., Perez-Riverol, Y. et al. lesSDRF is more: maximizing the value of proteomics data through streamlined metadata annotation. Nat Commun 14, 6743 (2023). https://doi.org/10.1038/s41467-023-42543-5

This application was not uploaded by the author, but through their publicly available Github repository, https://github.com/compomics/lesSDRF.

Prototype

Warning: Not intended for clinical use. Assume outputs are unsafe and unvalidated. Use carefully.


  • Favorites: 0
  • Executions: 46

  • Clinical Informatics

Owner

C Community Discovery

Member since