CMMC Validation

This repository contains the code for the CMMC data validator. You can validate your data prior to deposition by accessing CMMC Validation.

Table of Contents

• Features
• Requirements
• Installation
• Usage
• Cloud Application
• Valid Entries
• Troubleshooting

Features

• Case-insensitive validation for the following fields:
  • input_molecule_origin
  • input_confirmation
  • input_source
• API validation for SMILES strings and USIs.
• Outputs detailed error messages for invalid rows.
• Cloud-hosted Streamlit app for convenient use without local installation.

Requirements

• Python 3.7 or higher
• The following Python libraries:
  • pandas
  • requests
  • streamlit (optional, if you want to run the Streamlit app locally)

Installation

1. Clone the repository to your local machine:

   git clone https://github.com/wilhan-nunes/usi-smiles-validator.git

2. Navigate to the project directory:

   cd usi-smiles-validator

3. Install the required Python packages:

   pip install -r requirements.txt

Usage

To validate the deposition dataset, prepare a TSV file using the following template. The columns that will be validated are:

• input_usi
• input_structure
• input_molecule_origin
• input_confirmation
• input_source

Example script usage:

This will run the app locally:

streamlit run app.py

Cloud Application

You can also use the cloud-hosted Streamlit application to perform validation without needing to install anything locally.

Access the app here: CMMC Validation

Valid Entries

You can check the valid entries in the controlled_vocabulary.tsv file.

Troubleshooting

If you encounter any issues, here are a few tips:

• Case-sensitivity: The script performs case-insensitive validation, but make sure to remove any unnecessary spaces in the TSV file.
• SMILES validation errors: If you receive errors during SMILES validation, ensure that your SMILES strings are formatted correctly AND are valid. Use https://structure.gnps2.org/convert?smiles={your_smiles} replacing {your_smiles} with the appropriate value.
• USI validation: Ensure that the USI strings follow the correct format. The script allows multiple USIs separated by semicolons. If the HTTP response code that caused the failing is 500, the USI is probably valid, but the server faced some internal issue. Please, verify manually if this is the case accessing https://metabolomics-usi.gnps2.org/json/?usi1={your_500_code_usi} replacing {your_500_code_usi} with the appropriate value. If the page loads with a peak list, you are good to go.

If problems persist, please open an issue in the GitHub repository.