  Motivation: Our goal was to combine the capabilities of Spark and GOR into a
single computing framework for use in analysis of large scale genome data.
  Results: We have created a relational query engine that unites SparkSQL and
GORpipe into a single declarative query framework. This has been achieved by
allowing embedding of SQL expressions into the high-level relational statement
syntax in GOR and by supporting virtual relations and nested GORpipe
expressions within SQL. Furthermore, we have built drivers to enable Spark and
GOR to use and leverage their preferred file formats, Parquet and GORZ
respectively, and introduced APIs to allow the use of GOR with Spark
dataframes.
  Availability: The SparkGOR version of the GORpipe software is open-source and
freely available at https://gorpipe-website.now.sh and
https://github.com/gorpipe.
