Seqera Platform Feature Requests

We do not possess a full-blown LIMS and hope the Seqera Platform could provide some necessary dataset management features. The Datasets file management seems like a step in that direction, but we'd need to be able to search by field, automate dataset creation/deletion and map sequencing runs to samples . Specifically, we want to: Organize datasets by project (hierarchical or by label). Link from datasets to analysis runs on that data. A way to associate metadata (a location or a reference ID to another database) with a dataset as a whole, rather than each line inside the CSV file, and then manage that through the CLI/API and use it in a Nextflow pipeline run.

Uploading files to Seqera Platform datasets to run a workflow with simple file content adds an unnecessary complexity to our usage patterns. This is particularly pronounced when using the fetchngs workflow, for example where a single identifier may be all that's required. We still have to write that identifier to a file and upload it to a dataset before it can be used in a workflow. It would be great if a text box in the UI could be optionally used to supply file content, written to a file (and dataset?) behind the scenes, resulting in a reduced number of steps to run workflows.

The interaction with the dataset feature can be improved to enhance the user experience. Here some potential improvements: Enhanced Search Box : The search box could enable the filtering of datasets based on file types, such as CSV, TSV, and more. Pagination for Datasets : Pagination could improve the user experience when dealing with a large number of datasets. Dataset-Pipeline Association : Users could associate a dataset with a pipeline in both Launchpad and Actions, enhancing the integration and utility of datasets in the platform. No Dataset Matching Message : When there are no datasets matching the pipeline specification (schema file), display a dropdown with the message to inform the users. Dataset Version Dropdown : The dropdown for dataset versions could include the "Date edited" for added context. Labeling Datasets : To streamline the collation of resources associated with a specific study, it could be beneficial to allow datasets to be labeled with study identifiers.