ArticleNature communications2018
Uncovering pseudotemporal trajectories with covariates from single cell and bulk expression data.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers, 1 of them a synthesis that pooled it.
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Who cites it
76 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application.Molecular neurodegeneration · 2022Pooled it
- Article
- Finetuning Foundation Models for Temporal Clinical Transcriptomics Data.Bioinformatics (Oxford, England) · 2026Article
- Single-Cell RNA Sequencing Reveals the Heterogeneity and Microenvironment of Temporal Bone Squamous Cell Carcinoma.Clinical and experimental otorhinolaryngology · 2026Article
- Integrated transcriptomic analysis identifies an AKT1-associated metabolic-inflammatory signature in osteoporosis.Clinical and experimental medicine · 2026Article
- Associations of stable psychological traits with multi-omic subtypes of Alzheimer's dementia.Translational psychiatry · 2026Article
- Inferring stochastic dynamics by biophysical Neural ODE using single-cell transcriptomics.Nature communications · 2026Article
- Interpretable learning of temporal cellular dynamics from single-cell data.Cell reports methods · 2026Article
- Tumor prognostic risk stratification based on pseudo-time analysis of single-cell sequencing for patients with lung adenocarcinoma.Journal of thoracic disease · 2025Article
- A supervised Bayesian method for time (re)annotation of transcriptomics data.NAR genomics and bioinformatics · 2025Article
- Biomaterial-mediated Cell Atlas: an insight from single-cell and spatial transcriptomics.Bioactive materials · 2025Review
- Plasma proteomic Alzheimer's risk score: Biological age clock and pseudotime trajectory.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Early establishment and life course stability of sex biases in the human brain transcriptome.Cell genomics · 2025Article
- A temporal model of tumor-immune dynamics during the metastatic progression of high-grade serous ovarian cancer.NPJ precision oncology · 2025Article
- SKA1 promotes oncogenic properties in oral dysplasia and oral squamous cell carcinoma, and augments resistance to radiotherapy.Molecular oncology · 2025Article
- Maternal epigenetic index links early neglect to later neglectful care and other psychopathological, cognitive, and bonding effects.Clinical epigenetics · 2025Article
- Multi-modal Imaging-based Pseudotime Analysis of Alzheimer progression.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2025Article
- Prognostic value of pseudotime from texture parameters of FDG PET/CT in locally advanced rectal cancer with neoadjuvant concurrent chemoradiotherapy.Scientific reports · 2024Article
- Integrating amyloid imaging and genetics for early risk stratification of Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Article
16 more citing papers are in PubMed but not listed here.
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2 authors.
Funding
Abstract
Pseudotime algorithms can be employed to extract latent temporal information from cross-sectional data sets allowing dynamic biological processes to be studied in situations where the collection of time series data is challenging or prohibitive. Computational techniques have arisen from single-cell 'omics and cancer modelling where pseudotime can be used to learn about cellular differentiation or tumour progression. However, methods to date typically implicitly assume homogeneous genetic, phenotypic or environmental backgrounds, which becomes limiting as data sets grow in size and complexity. We describe a novel statistical framework that learns how pseudotime trajectories can be modulated through covariates that encode such factors. We apply this model to both single-cell and bulk gene expression data sets and show that the approach can recover known and novel covariate-pseudotime interaction effects. This hybrid regression-latent variable model framework extends pseudotemporal modelling from its most prevalent area of single cell genomics to wider applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.