MOTIVATION: Segmentation and automated genome annotation (SAGA) techniques, such as Segway and ChromHMM, assign labels to every part of the genome, identifying similar patterns across multiple genomic input signals. Inferring biological meaning in these patterns remains challenging. Doing so requires a time-consuming process of manually downloading reference data, running multiple analysis methods, and interpreting many individual results. RESULTS: To simplify these tasks, we developed the turnkey system Segzoo. As input, Segzoo only requires a genome annotation file in browser extensible data (BED) format. It automatically downloads the rest of the data required for comparisons. Segzoo performs analyses using these data and summarizes results in a single visualization. AVAILABILITY AND IMPLEMENTATION: The source code for Python ≥ 3.7 on Linux is freely available for download at https://github.com/hoffmangroup/segzoo under the GNU General Public License (GPL) version 2. Segzoo is also available in the Bioconda package segzoo: https://anaconda.org/bioconda/segzoo. We have deposited in Zenodo the version of the Segzoo source which produced the results in this article (https://doi.org/10.5281/zenodo.10988775), other code and data used to produce the results (https://doi.org/10.5281/zenodo.10477083), and the results (https://doi.org/10.5281/zenodo.10477106).