The changelog can be found here: https://feedback.nygen.io/changelog
How often are new features added to the platform?
We regularly update and improve our platform to meet the evolving needs of our users and to stay at the forefront of single-cell genomics analysis. Typically, we release minor updates and bug fixes every week, while larger feature updates are rolled out every month. However, the exact frequency can vary depending on the complexity of the features and user feedback.
Can users request new features?
Yes, we strongly encourage user feedback and feature requests. User needs and suggestions significantly influence our development roadmap. Users can submit feature requests through various channels:
- Directly through the platform's feedback mechanism: https://feedback.nygen.io/
- By contacting our support team at support@nygen.io
- During regular check-ins with our customer success team.
We carefully review all requests and prioritize them based on user demand, technical feasibility, and alignment with our overall platform strategy.
Is there a roadmap for future developments?
Yes, we maintain a development roadmap that outlines our plans for future features and improvements. While we don't publicly share the entire roadmap to maintain flexibility and competitive advantage, we do communicate major upcoming features to our users through:
- Regular product update newsletters
- Announcements within the platform
- Our official blog and social media channels
We also provide more detailed roadmap information to our enterprise customers during periodic review meetings.
How do you handle backward compatibility with older datasets?
Maintaining backward compatibility is a key priority to ensure that our users' historical data and analyses remain accessible and functional. Here's how we approach this:
- Version Control: We implement strict version control for our data formats and analysis algorithms. This allows us to track changes and maintain support for older versions.
- Data Migration: When significant changes are made to our data structures, we provide automated migration tools to update older datasets to the new format, ensuring they remain compatible with the latest features.
- Clear Documentation: We provide clear documentation on any changes that might affect older datasets, including instructions on how to update or adapt analyses if necessary.
- Gradual Rollout: For major changes that might affect backward compatibility, we often implement a gradual rollout with an overlap period during which both old and new systems are supported, allowing users time to transition.
- User Notifications: We proactively notify users if any of their datasets or analyses might be affected by upcoming changes, providing guidance on any actions they need to take.
- Testing: Before rolling out any updates, we extensively test with a wide range of dataset types and ages to ensure continued compatibility.