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Updated: Jul 3, 2025

Robust 3D DNA FISH Using Directly Labeled Probes

Robust 3D DNA FISH Using Directly Labeled Probes

Published on: August 15, 2013

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

Xavier Devos¹, Jean-Bernard Fiche¹, Marion Bardou¹

¹Centre de Biologie Structurale, Univ Montpellier, CNRS UMR 5048, INSERM U1054, 34090, Montpellier, France.

|February 13, 2024

Summary

This summary is machine-generated.

New imaging-based spatial genomics methods overcome limitations of sequencing. We present pyHiM, a Python toolbox for analyzing multiplexed DNA-FISH data and reconstructing single-cell chromatin organization.

Keywords:

3D chromatin structure Bioimage informatics Imaging Spatial genomics Transcription

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Area of Science:

Genomics
Cell Biology
Bioinformatics

Background:

Genome-wide ensemble sequencing provides insights into chromatin organization but cannot resolve single-cell heterogeneity or spatial arrangements.
Emerging imaging-based techniques are advancing the field of spatial genomics by enabling visualization of molecular structures within cells.

Purpose of the Study:

To introduce pyHiM, a user-friendly Python toolbox for analyzing multiplexed DNA-FISH data.
To enable the reconstruction of chromatin traces in individual cells, addressing limitations of traditional sequencing methods.
To facilitate the democratization and standardization of spatial genomics data analysis.

Main Methods:

Development of pyHiM, a Python toolbox with a modular architecture.
Utilizing multiplexed DNA-FISH (Fluorescence In Situ Hybridization) data for analysis.
Implementing algorithms for chromatin trace reconstruction in individual cells.

Main Results:

pyHiM offers a user-friendly interface for spatial genomics data analysis.
The toolbox allows for independent execution and customization of analysis steps.
Enables detailed reconstruction of chromatin organization at the single-cell level.

Conclusions:

pyHiM enhances the analysis of spatial genomics data, particularly multiplexed DNA-FISH.
The toolbox promotes wider accessibility and standardization in the field of spatial genomics.
Facilitates a deeper understanding of single-cell chromatin organization and heterogeneity.