Seqera Platform Feature Requests

Anonymous

Feature requests for the Seqera Platform (https://cloud.seqera.io)
Run Detail Page Improvements
Enhance the user experience by improving the widgets on the run detail page without altering user flows. The primary goals of this UI update are: Improve the entire page's layout by reorganizing the order of widgets and the information within them. Unify color and icon use to ensure consistency across the application. Specifically: To enhance the usability and aesthetics of the "General" widget in run detail page, improvements will involve reordering and resizing elements, optimizing the widget for increased interactive intuitiveness, unifying icon styles to outline format, and introducing an expand/collapse functionality. This aims to address the visual imbalance caused by the increased elements such as resource labels, pipeline name, and optimization details within the widget. The current Process widget layout presents problems because the names can be too long and unreadable, the numeric value is unclear, and the progress bar lacks clarity. We aim to improve this by resizing and restyling the Process widget, providing an easy way to jump into tasks, and evaluate an overall progress indicator for added clarity. Improve the Status widget UI on the run detail page, enhancing accessibility by adjusting text color contrast, consolidating the use of colors, especially for the "Cached" status, and renaming the widget to accurately reflect its content: "Task status." These changes aim to enhance user experience and clarity in interpreting the widget information. The Tasks table enhancement is addressed in a separate effort.
20
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in progress

Datasets improvements
Datasets within Seqera Platform facilitate structured handling of input sample sheets required for genomics pipelines such as RNA-seq. Currently, researchers often face friction in assembling these datasets, needing to prepare CSV files externally. This could be improved by the following: 1. Remove Dataset limit: Users are currently limited to 1000 datasets per workspace. Action: Raise or remove limit 2. Dataset creation from Pipeline Launch UI: Currently, creating datasets requires users to navigate away from the pipeline launch page, disrupting workflow and causing friction. Action: Integrate dataset creation directly within the pipeline launch interface, users can seamlessly upload or enter sample data without leaving their primary task. 3. Improved Dataset listing: Currently, the dataset listing is relatively basic and low density. Around 6 datasets can be viewed in a typical desktop browser window size. This density plus lack of tooling hinders users from effectively navigating or identifying datasets quickly. Action: A metadata-rich table view, such as those used on the Runs page and elsewhere would be preferable. Such a table could include the dataset name, number of rows, author, creation date, last used date, and potentially the start of the description. The table will be sortable. 4. Keep a record of Dataset usage in Runs: Currently, it’s difficult / impossible to know if a dataset has ever been used. This makes their utility post-usage very limited. Action: With a record of Dataset usage within Run history, Datasets suddenly become a powerful tool for the user. They act as a rich history of run inputs, agnostic to the specifics of pipeline design and file usage. 5. Enhanced Dataset details user interface: Currently, viewing dataset details emphasizes metadata over actual dataset content, causing users unnecessary scrolling and inefficiency. Action: Prioritizing the dataset’s actual content prominently at the top ensures users quickly verify the dataset's accuracy and completeness, reducing errors and improving productivity. 6. Manual inline Dataset editing: Users currently must create or edit sample sheets externally, and upload these files to create or edit Datasets, which is inefficient. Action: An embedded spreadsheet editor within the platform would allow users to quickly and intuitively enter data and make edits directly. 7. "Archive" or "deactivate" a Dataset: Datasets are often used once or twice, and then no longer actively needed. For GxP/clinical environments, the dataset should not be deleted/removed, but made inactive/disabled/"archived"/"deactivated". This allows inspection of the dataset, but it would be excluded from any pipeline launches. The table of datasets can be filtered to remove inactive/disabled/"archived"/"deactivated" entries. Action: Allow datasets to be tagged as “inactive/disabled/archived/deactivated” and allow filtering of datasets to show/hide archived entries. 8. Support for YAML and JSON formatted data: Support for non-tabular datasets (eg. arbitrary YAML and JSON) is useful for users. Action: Allow upload and editing of YAML and JSON datasets. Future potential milestones: Integration with new Nextflow data lineage
7
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evaluating

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