Quon, J. | Search bioRxiv

bioRxiv2025

Epilogos: information-theoretic navigation of multi-tissue functional genomic annotations

Functional genomics data, such as chromatin state maps, provide critical insights into biological processes, but are hard to navigate and interpret. We present Epilogos to address this challenge by offering a simple information-theoretic framework for large-scale visualization, navigation and interpretation of functional genomics annotations, and apply it to over 2,000 genome-wide chromatin state maps in human and mouse. We construct intuitive visualizations of multi-tissue chromatin state maps, prioritize salient genomic regions, identify group-wise differential regions, and enable rapid similarity search given a region of interest. To facilitate usability, we provide a purpose-built web-based browser interface (http://epilogos.net) alongside open-source software for community access and adoption.

genomics↗

bioRxiv2024

MerQuaCo: a computational tool for quality control in image-based spatial transcriptomics

Image-based spatial transcriptomics platforms are powerful tools often used to identify cell populations and describe gene expression in intact tissue. Spatial experiments return large, high-dimensional datasets and several open-source software packages are available to facilitate analysis and visualization. The outputs of spatial transcriptomics platforms are typically imperfect. For example, local variations in transcript detection probability are common. Software tools to characterize imperfections and their impact on downstream analyses are lacking so the data quality is assessed manually, a laborious and often a subjective process. Here we describe imperfections in a dataset of 641 fresh-frozen adult mouse brain sections collected using the Vizgen MERSCOPE. Common imperfections included the local loss of tissue from the section, tissue outside the imaging volume due to detachment from the coverslip, transcripts missing due to dropped images, varying detection probability through space, and differences in transcript detection probability between experiments. We describe the incidence of each imperfection and the likely impact on the accuracy of cell type labels. We develop MerQuaCo, open-source code that detects and quantifies imperfections without user input, facilitating the selection of sections for further analysis with existing packages. Together, our results and MerQuaCo facilitate rigorous, objective assessment of the quality of spatial transcriptomics results.

bioinformatics↗