Once the data has been loaded into BigQuery, we can perform some filtering to identify data of sufficient quality to be used in downstream analyses.
(1) Identify passing cells by running queries cell_metrics.sql and passing_cells.sql and materializing the result to new BigQuery tables.
(2) Identify passing genes by running queries gene_metrics.sql and passing_genes.sql and materializing the result to new BigQuery tables.
As an example, QualityControl.Rmd has been provided to show the process end-to-end, but these queries can also be run manually in the BigQuery Web UI, via the bq command line tool, etc... Just edit anything you see in {{ JINJA MARKUP }} to be the actual tables you want to use.
To run the BigQuery query integration tests:
- Install the test
framework
via
pip install git+https://github.com/verilylifesciences/[email protected] - and then run the test like so
python cell_metrics_test.py