Idea - Considerations from start to finish

[DrK-Lo]

At the Training and Integration Workshop, we talked about having a overview page about considerations for sequencing from start to finish. This is not highly detailed, but just a list of guidelines for a newcomer to think about and links to more information if needed.

Pre-sequencing

1. Collecting data in a way so it can be easily integrated later
2. Extraction nuances
3. Randomizing samples on plates to reduce batch effects
4. Quantifying libraries with qPCR prior to sequencing to ensure you will get reads back
5. Sample storage

Post-sequencing
6. When to submit sequencing to public repository / where to submit / what metadata to include (I liked the suggestion that we should submit right away with an embargo)
6. Data storage
7. Conda environments
8. Intermediate data products to save
9. Recommended intermediate data products to archive with publication

[DrK-Lo]

I can now add to this "Using apps to collect and organize data"