2026-07-15 –, University Hall
Genomic workflows remain tightly coupled to specialized file formats, forcing researchers to build brittle pipelines of format-specific CLI tools. We present projects that help shift this emphasis away from file parsing and towards declarative querying. Oxbow is a library that projects common genomic formats into Apache Arrow, enabling zero-copy integration with data frame libraries and analytics engines. GIQL (Genomic Interval Query Language) is an extended SQL dialect supporting genomic interval operations and semantics that transpiles to standard SQL, making genomic queries composable, readable, and backend-agnostic. Together, this architecture also facilitates the integration of genomic data into data warehouse and lakehouse platforms as well as agentic MCP workflows.
Genomic data tools remain tightly coupled to specialized file formats, forcing researchers to build brittle pipelines of format-specific CLI tools connected by ad hoc serialization. Meanwhile, standard SQL -- the lingua franca of data analytics -- lacks the vocabulary to express genomic interval relationships and operations that are fundamental to the field. To address both of these issues, we present a pair of projects that together shift the emphasis in genomics from file parsing towards declarative querying.
The first project, Oxbow, is a Rust-based adapter library that projects common genomic file formats, including BAM, VCF, BED, GTF, BigWig, and others, into Apache Arrow, a standard columnar in-memory representation for tabular analytics. By leveraging Arrow's C Data Interface, Oxbow streams records to Python with zero copy overhead, integrating directly with Polars, DuckDB, and Dask without intermediate serialization. Oxbow supports indexed range queries, column projection push-down, and remote data access via HTTP and object storage, enabling researchers to query genomic files hosted in the cloud without downloading them locally.
The second project, GIQL (Genomic Interval Query Language, pronounced “JEE-quel”) is an extended SQL dialect and transpiler for genomic interval operations. GIQL introduces domain-specific operators, such as INTERSECTS, WITHIN, and NEAREST, that let researchers express genomic interval logic and spatial joins declaratively. For example, WHERE a.interval INTERSECTS b.interval transpiles into standard SQL predicates that any engine can execute. Because the transpiler targets standard SQL, it is backend-agnostic: the same query runs on DuckDB, Polars, SQLite, or any SQL-compliant engine. GIQL provides a declarative alternative to bedtools-style scripting, making genomic queries composable, readable, and reproducible.
These libraries work together, where Oxbow streams legacy genomic files as Arrow record batches into a SQL engine, and GIQL provides the extended query semantics to interrogate them. We will demonstrate this composition in practice. By building on open, domain-agnostic standards, this architecture also facilitates the integration of genomic data into modern data warehouse and lakehouse platforms as well as agentic MCP workflows.
I am an Assistant Professor in the Department of Genomics and Computational Biology and the Department of Systems Biology at UMass Chan Medical School.
I lead a computational research group (https://abdenlab.org) with a dual mandate. My group's biological research focuses on the 3D organization of the genome (3C/Hi-C technologies), its relationship to the epigenome, and the resulting manifold influences on cellular fate, differentiation, aging, and disease. My group's open-source interests are in supporting foundational infrastructure to improve AI and data science for genomics and multi-omics, especially in the scientific Python ecosystem.
