pyHiM: a new open-source, multi-platform software package for spatial genomics based on multiplexed DNA-FISH imaging.

Genome-wide ensemble sequencing methods improved our understanding of chromatin organization in eukaryotes but lack the ability to capture single-cell heterogeneity and spatial organization. To overcome these limitations, new imaging-based methods have emerged, giving rise to the field of spatial genomics. Here, we present pyHiM, a user-friendly python toolbox specifically designed for the analysis of multiplexed DNA-FISH data and the reconstruction of chromatin traces in individual cells. pyHiM employs a modular architecture, allowing independent execution of analysis steps and customization according to sample specificity and computing resources. pyHiM aims to facilitate the democratization and standardization of spatial genomics analysis.

Qudi-HiM: an open-source acquisition software package for highly multiplexed sequential and combinatorial optical imaging.

Multiplexed sequential and combinatorial imaging enables the simultaneous detection of multiple biological molecules, e.g. proteins, DNA, or RNA, enabling single-cell spatial multi-omics measurements at sub-cellular resolution. Recently, we designed a multiplexed imaging approach (Hi-M) to study the spatial organization of chromatin in single cells. In order to enable Hi-M sequential imaging on custom microscope setups, we developed Qudi-HiM, a modular software package written in Python 3. Qudi-HiM contains modules to automate the robust acquisition of thousands of three-dimensional multicolor microscopy images, the handling of microfluidics devices, and the remote monitoring of ongoing acquisitions and real-time analysis. In addition, Qudi-HiM can be used as a stand-alone tool for other imaging modalities.