ArticleGenome biology2018
BGP: identifying gene-specific branching dynamics from single-cell data with a branching Gaussian process.
Article in Genome biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Bayesian inference of haematopoietic stem/progenitor cell differentiation phenotypic manifolds and their bifurcation points using Gaussian processes and Gibbs sampling.Scientific reports · 2026Article
- Branch-specific gene discovery in cell differentiation using multi-omics graph attention.PLoS computational biology · 2025Article
- Revealing gene function with statistical inference at single-cell resolution.Nature reviews. Genetics · 2024Review
- scapGNN: A graph neural network-based framework for active pathway and gene module inference from single-cell multi-omics data.PLoS biology · 2023Article
- A single-cell transcriptomic landscape of mouse testicular aging.Journal of advanced research · 2023Article
- An integrated atlas of human placental development delineates essential regulators of trophoblast stem cells.Development (Cambridge, England) · 2022Article
- Representation learning of RNA velocity reveals robust cell transitions.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Non-parametric modelling of temporal and spatial counts data from RNA-seq experiments.Bioinformatics (Oxford, England) · 2021Article
- A Bayesian semi-parametric model for thermal proteome profiling.Communications biology · 2021Article
- A statistical framework for assessing pharmacological responses and biomarkers using uncertainty estimates.eLife · 2020Article
- Dynamical gene regulatory networks are tuned by transcriptional autoregulation with microRNA feedback.Scientific reports · 2020Article
- Trajectory-based differential expression analysis for single-cell sequencing data.Nature communications · 2020Article
- Bayesian statistical learning for big data biology.Biophysical reviews · 2019Review
- BGP: identifying gene-specific branching dynamics from single-cell data with a branching Gaussian process.Genome biology · 2018Article
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Authors and funding
3 authors.
Funding
Abstract
High-throughput single-cell gene expression experiments can be used to uncover branching dynamics in cell populations undergoing differentiation through pseudotime methods. We develop the branching Gaussian process (BGP), a non-parametric model that is able to identify branching dynamics for individual genes and provide an estimate of branching times for each gene with an associated credible region. We demonstrate the effectiveness of our method on simulated data, a single-cell RNA-seq haematopoiesis study and mouse embryonic stem cells generated using droplet barcoding. The method is robust to high levels of technical variation and dropout, which are common in single-cell data.
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Registered trials
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