pyHiM: a new open-source, multi-platform software package for spatial genomics based on multiplexed DNA-FISH imaging.
Xavier DevosJean-Bernard FicheMarion BardouOlivier MessinaChristophe HoubronJulian GurgoMarie SchaefferMarkus GötzThomas WalterFlorian MuellerMarcelo NollmannPublished in: Genome biology (2024)
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.
Keyphrases
- single cell
- rna seq
- genome wide
- high throughput
- high resolution
- dna damage
- gene expression
- induced apoptosis
- transcription factor
- single molecule
- dna methylation
- cell free
- big data
- oxidative stress
- photodynamic therapy
- data analysis
- machine learning
- artificial intelligence
- cell death
- endoplasmic reticulum stress
- nucleic acid
- circulating tumor cells
- cell proliferation
- fluorescence imaging
- neural network