ksuderman / experiments Goto Github PK

Find interesting datasets for the benchmarking workflows. An interesting dataset is simply one that is large enough (a few gigabytes or larger) to provide meaningful runtimes.

For each dataset we need to:

1. Identify and document the original source of the data.
2. Load the data into usegalaxy.org and export the history.
3. Upload the exported history to our Amazon S3 bucket.

Defined and implement the Galaxy workflows needed for benchmarking experiments.

• DNA Single Reads
• DNA Paired Reads
• Variant Calling
• RNA-Seq

The run summary data is generated from the all.csv file by a Python script and then pushed to GitHub. It would be nice to generate this directly from the all.csv file Observable and omit the extra step of running the Python script.