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Uncovering pseudotemporal trajectories with covariates from single cell and bulk expression data

Nature communications, 2018-06, Vol.9 (1), p.2442-12, Article 2442

2018

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Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R

Bioinformatics (Oxford, England), 2017-04, Vol.33 (8), p.1179-1186

2017

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Order Under Uncertainty: Robust Differential Expression Analysis Using Probabilistic Models for Pseudotime Inference

PLoS computational biology, 2016-11, Vol.12 (11), p.e1005212-e1005212

2016

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Beyond benchmarking and towards predictive models of dataset-specific single-cell RNA-seq pipeline performance

Genome Biology, 2024-06, Vol.25 (1), p.1-18

2024

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Probabilistic cell-type assignment of single-cell RNA-seq for tumor microenvironment profiling

Nature methods, 2019-10, Vol.16 (10), p.1007-1015

2019

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The impacts of active and self-supervised learning on efficient annotation of single-cell expression data

Nature communications, 2024-02, Vol.15 (1), p.1014-1014, Article 1014

2024

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Dissociation of solid tumor tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses

Genome Biology, 2019-10, Vol.20 (1), p.210-210, Article 210

2019

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clonealign: statistical integration of independent single-cell RNA and DNA sequencing data from human cancers

Genome Biology, 2019-03, Vol.20 (1), p.54-54, Article 54

2019

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Single-cell decoding of drug induced transcriptomic reprogramming in triple negative breast cancers

Genome Biology, 2024-07, Vol.25 (1), p.1-32, Article 191

2024

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A descriptive marker gene approach to single-cell pseudotime inference

Bioinformatics, 2019-01, Vol.35 (1), p.28-35

2019

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Probabilistic modeling of bifurcations in single-cell gene expression data using a Bayesian mixture of factor analyzers

Wellcome open research, 2017-03, Vol.2, p.19-19

2017

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switchde: inference of switch-like differential expression along single-cell trajectories

Bioinformatics (Oxford, England), 2017-04, Vol.33 (8), p.1241-1242

2017

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Eleven grand challenges in single-cell data science

Genome Biology, 2020-02, Vol.21 (1), p.31-35, Article 31

2020

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Characterizing the impacts of dataset imbalance on single-cell data integration

Nature biotechnology, 2024-03

2024

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Single-Cell Sequencing of iPSC-Dopamine Neurons Reconstructs Disease Progression and Identifies HDAC4 as a Regulator of Parkinson Cell Phenotypes

Cell stem cell, 2019-01, Vol.24 (1), p.93-106.e6

2019

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The Landscape of COVID-19 Research in the United States: a Cross-sectional Study of Randomized Trials Registered on ClinicalTrials.Gov

Journal of general internal medicine : JGIM, 2022-01, Vol.37 (1), p.154-161

2022

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Loss of apelin blocks the emergence of sprouting angiogenesis in experimental tumors

The FASEB journal, 2022-10, Vol.36 (10), p.e22560-n/a

2022

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Radiomics analysis to predict pulmonary nodule malignancy using machine learning approaches

Thorax, 2024-03, Vol.79 (4), p.307-315

2024

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Computational modelling in single-cell cancer genomics: methods and future directions

Physical biology, 2020-11, Vol.17 (6), p.061001-061001

2020

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Automated assignment of cell identity from single-cell multiplexed imaging and proteomic data

Cell systems, 2021-12, Vol.12 (12), p.1173-1186.e5

2021

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The Basics of Machine Learning

NEJM evidence, 2022-05, Vol.1 (5)

2022

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Single cell transcriptomes of normal endometrial derived organoids uncover novel cell type markers and cryptic differentiation of primary tumours

The Journal of pathology, 2020-10, Vol.252 (2), p.201-214

2020

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Modelling hereditary diffuse gastric cancer initiation using transgenic mouse‐derived gastric organoids and single‐cell sequencing

The Journal of pathology, 2021-07, Vol.254 (3), p.254-264

2021

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Clonal fitness inferred from time-series modelling of single-cell cancer genomes

Nature (London), 2021-07, Vol.595 (7868), p.585-590

2021

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Abstract 4706: Temperature-dependent transcription artifacts and cell population biases in scRNAseq data are minimized by tissue dissociation at low temperatures

Cancer research (Chicago, Ill.), 2019-07, Vol.79 (13_Supplement), p.4706-4706

2019

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Uncovering pseudotemporal trajectories with covariates from single cell and bulk expression data

Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R

Order Under Uncertainty: Robust Differential Expression Analysis Using Probabilistic Models for Pseudotime Inference

Beyond benchmarking and towards predictive models of dataset-specific single-cell RNA-seq pipeline performance

Probabilistic cell-type assignment of single-cell RNA-seq for tumor microenvironment profiling

The impacts of active and self-supervised learning on efficient annotation of single-cell expression data

Dissociation of solid tumor tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses

clonealign: statistical integration of independent single-cell RNA and DNA sequencing data from human cancers

Single-cell decoding of drug induced transcriptomic reprogramming in triple negative breast cancers

A descriptive marker gene approach to single-cell pseudotime inference

Probabilistic modeling of bifurcations in single-cell gene expression data using a Bayesian mixture of factor analyzers

switchde: inference of switch-like differential expression along single-cell trajectories

Eleven grand challenges in single-cell data science

Characterizing the impacts of dataset imbalance on single-cell data integration

Single-Cell Sequencing of iPSC-Dopamine Neurons Reconstructs Disease Progression and Identifies HDAC4 as a Regulator of Parkinson Cell Phenotypes

The Landscape of COVID-19 Research in the United States: a Cross-sectional Study of Randomized Trials Registered on ClinicalTrials.Gov

Loss of apelin blocks the emergence of sprouting angiogenesis in experimental tumors

Radiomics analysis to predict pulmonary nodule malignancy using machine learning approaches

Computational modelling in single-cell cancer genomics: methods and future directions

Automated assignment of cell identity from single-cell multiplexed imaging and proteomic data

The Basics of Machine Learning

Single cell transcriptomes of normal endometrial derived organoids uncover novel cell type markers and cryptic differentiation of primary tumours

Modelling hereditary diffuse gastric cancer initiation using transgenic mouse‐derived gastric organoids and single‐cell sequencing

Clonal fitness inferred from time-series modelling of single-cell cancer genomes

Abstract 4706: Temperature-dependent transcription artifacts and cell population biases in scRNAseq data are minimized by tissue dissociation at low temperatures

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