Journal
BIOINFORMATICS
Volume 38, Issue 23, Pages 5151-5159Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btac670
Keywords
-
Categories
Funding
- Fundamental Research Funds for the Central Universities [xzy012022087]
- National Natural Science Foundation of China [61602367]
Ask authors/readers for more resources
scHiCPTR is an unsupervised graph-based algorithm for inferring pseudotime from single-cell Hi-C contact matrices. It achieves high performance in pseudotime inference and exhibits reasonable biological significance by optimizing graph structure and handling developmental trajectories with multiple topologies.
Motivation: The emerging single-cell Hi-C technology provides opportunities to study dynamics of chromosomal organization. How to construct a pseudotime path using single-cell Hi-C contact matrices to order cells along developmental trajectory is a challenging topic, since these matrices produced by the technology are inherently high dimensional and sparse, they suffer from noises and biases, and the topology of trajectory underlying them may be diverse. Results: We present scHiCPTR, an unsupervised graph-based pipeline to infer pseudotime from single-cell Hi-C contact matrices. It provides a workflow consisting of imputation and embedding, graph construction, dual graph refinement, pseudotime calculation and result visualization. Beyond the few existing methods, scHiCPTR ties to optimize graph structure by two parallel procedures of graph pruning, which help reduce the spurious cell links resulted from noises and determine a global developmental directionality. Besides, it has an ability to handle developmental trajectories with multiple topologies, including linear, bifurcated and circular ones, and is competitive with methods developed for single-cell RNA-seq data. The comparative results tell that our scHiCPTR can achieve higher performance in pseudotime inference, and the inferred developmental trajectory exhibit a reasonable biological significance.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available