scGHOST: identifying single-cell 3D genome subcompartments.
Kyle XiongRuochi ZhangJian MaPublished in: Nature methods (2024)
Single-cell Hi-C (scHi-C) technologies allow for probing of genome-wide cell-to-cell variability in three-dimensional (3D) genome organization from individual cells. Computational methods have been developed to reveal single-cell 3D genome features based on scHi-C, including A/B compartments, topologically associating domains and chromatin loops. However, no method exists for annotating single-cell subcompartments, which is important for understanding chromosome spatial localization in single cells. Here we present scGHOST, a single-cell subcompartment annotation method using graph embedding with constrained random walk sampling. Applications of scGHOST to scHi-C data and contact maps derived from single-cell 3D genome imaging demonstrate reliable identification of single-cell subcompartments, offering insights into cell-to-cell variability of nuclear subcompartments. Using scHi-C data from complex tissues, scGHOST identifies cell-type-specific or allele-specific subcompartments linked to gene transcription across various cell types and developmental stages, suggesting functional implications of single-cell subcompartments. scGHOST is an effective method for annotating single-cell 3D genome subcompartments in a broad range of biological contexts.
Keyphrases
- single cell
- rna seq
- genome wide
- high throughput
- dna methylation
- gene expression
- induced apoptosis
- high resolution
- transcription factor
- stem cells
- electronic health record
- big data
- machine learning
- cell therapy
- cell proliferation
- cell cycle arrest
- cell death
- pi k akt
- signaling pathway
- artificial intelligence
- data analysis