Article
Multidisciplinary Sciences
Chang Su, Zichun Xu, Xinning Shan, Biao Cai, Hongyu Zhao, Jingfei Zhang
Summary: The advancement of scRNA-seq technology enables the direct inference of co-expressions in specific cell types, but existing methods fail to address the challenges of sequencing depth variations and measurement errors. CS-CORE is a statistical approach that accurately estimates and tests cell-type-specific co-expressions while considering these challenges. Evaluations demonstrate that CS-CORE outperforms existing methods in terms of accuracy and identification of relevant co-expressions. Applied to scRNA-seq data from Alzheimer's disease and COVID-19 patients, CS-CORE identifies reproducible and biologically relevant cell-type-specific co-expressions and differential co-expressions.
NATURE COMMUNICATIONS
(2023)
Article
Biotechnology & Applied Microbiology
Michael A. Skinnider, Jordan W. Squair, Claudia Kathe, Mark A. Anderson, Matthieu Gautier, Kaya J. E. Matson, Marco Milano, Thomas H. Hutson, Quentin Barraud, Aaron A. Phillips, Leonard J. Foster, Gioele La Manno, Ariel J. Levine, Gregoire Courtine
Summary: The Augur method can effectively identify the cell types most responsive to biological perturbations in single-cell data, helping to explore the relationship between gene expression changes and biological functions.
NATURE BIOTECHNOLOGY
(2021)
Article
Health Care Sciences & Services
Wendao Liu, Noam Shomron
Summary: MicroRNAs regulate gene expression by binding to mRNAs, reducing target gene expression levels and noise. Single-cell RNA sequencing technology has been used to study miRNA and mRNA expression in single cells. However, technical noise from scRNA-seq can mask the effect of miRNAs on gene expression noise. Improvements in experimental design and computational analysis are necessary to reduce technical noise.
JOURNAL OF PERSONALIZED MEDICINE
(2022)
Article
Multidisciplinary Sciences
Peijie Zhou, Shuxiong Wang, Tiejun Li, Qing Nie
Summary: MuTrans is a method based on multiscale reduction technique that can identify the underlying stochastic dynamics governing cell-fate transitions, construct cell-fate dynamical manifold, distinguish stable and transition cells, and quantify transition probabilities between cell states. The method is consistent with Langevin equation and transition rate theory, and has been shown to robustly unravel complex cell fate dynamics induced by transition cells in various systems. It bridges data-driven and model-based approaches for single-cell resolution analysis of cell-fate transitions.
NATURE COMMUNICATIONS
(2021)
Article
Biochemical Research Methods
Matteo Borella, Graziano Martello, Davide Risso, Chiara Romualdi
Summary: Single-cell RNA sequencing provides a comprehensive view of tissue and organism development, but also presents computational challenges that require accurate and efficient solutions. In this study, the method PsiNorm based on power-law Pareto distribution is proposed as a highly scalable normalization method. Benchmarking against other methods shows that PsiNorm performs well in terms of cluster identification and scalability.
Article
Biochemistry & Molecular Biology
Mengting Huang, Yixuan Yang, Xingzhao Wen, Weiqiang Xu, Na Lu, Xiao Sun, Jing Tu, Zuhong Lu
Summary: Although single cell RNA sequencing technologies are well developed, acquiring large-scale single cell expression data can still be costly. The study proposes a method of compressing expression profiles from the sample dimension by assigning each cell into multiple pools and demonstrates that expression profiles can be inferred from pool expression data with a overlapping pooling design and compressed sensing strategy. This approach, when combined with plate-based scRNA-seq measurement, maintains superior gene detection sensitivity and individual identity while reducing library costs by half.
NUCLEIC ACIDS RESEARCH
(2021)
Article
Biochemical Research Methods
Fei Qin, Xizhi Luo, Feifei Xiao, Guoshuai Cai
Summary: This study developed a novel simulator for single-cell RNA sequencing (scRNA-seq) data that accurately captures important data features and performs well in recovering cell-cell distances. The simulator also helped evaluate differential expression analysis methods and identify the best-performing ones.
Article
Multidisciplinary Sciences
Joshua Burton, Cerys S. Manning, Magnus Rattray, Nancy Papalopulu, Jochen Kursawe
Summary: Gene expression dynamics, such as stochastic oscillations and aperiodic fluctuations, are associated with cell fate changes, and single-cell live imaging is widely used to observe these dynamics. However, investigating the regulatory mechanisms underlying these dynamics is challenging due to complex interactions of multiple processes.
JOURNAL OF THE ROYAL SOCIETY INTERFACE
(2021)
Article
Biochemistry & Molecular Biology
Anna Hendrika Cornelia Vlot, Setareh Maghsudi, Uwe Ohler
Summary: Identification of cell identity markers is crucial in single-cell omics data analysis. Existing methods rely on cluster assignments, but this approach is challenging for developmental data and often requires prior knowledge. In this study, we propose SEMITONES, a cluster-free marker identification method, and demonstrate its superior performance on multiple single-cell datasets.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Multidisciplinary Sciences
Jingyang Qian, Jie Liao, Ziqi Liu, Ying Chi, Yin Fang, Yanrong Zheng, Xin Shao, Bingqi Liu, Yongjin Cui, Wenbo Guo, Yining Hu, Hudong Bao, Penghui Yang, Qian Chen, Mingxiao Li, Bing Zhang, Xiaohui Fan
Summary: The single-cell RNA-seq technology eliminates the spatial information of individual cells, but we propose a method called scSpace, which reconstructs cells onto a pseudo-space using spatial transcriptome references to identify spatially variable cell subpopulations.
NATURE COMMUNICATIONS
(2023)
Article
Biochemistry & Molecular Biology
Xinan H. Yang, Andrew Goldstein, Yuxi Sun, Zhezhen Wang, Megan Wei, Ivan P. Moskowitz, John M. Cunningham
Summary: Single-cell transcriptome analysis is crucial for understanding cellular state transitions. BioTIP, utilizing tipping-point theory and feature selection, overcomes challenges in identifying critical transition signals and inferring lineage-determining transcription factors.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Multidisciplinary Sciences
Karren Dai Yang, Anastasiya Belyaeva, Saradha Venkatachalapathy, Karthik Damodaran, Abigail Katcoff, Adityanarayanan Radhakrishnan, G. Shivashankar, Caroline Uhler
Summary: The authors use autoencoders to learn a probabilistic coupling and map different data modalities to a shared latent space, presenting an approach for integrating vastly different modalities. The integration of imaging and transcriptomics is still an open challenge, but this method provides a framework for diverse applications in biomedical discovery.
NATURE COMMUNICATIONS
(2021)
Article
Biochemistry & Molecular Biology
Yuliangzi Sun, Woo Jun Shim, Sophie Shen, Enakshi Sinniah, Duy Pham, Zezhuo Su, Dalia Mizikovsky, Melanie D. White, Joshua W. K. Ho, Quan Nguyen, Mikael Boden, Nathan J. Palpant
Summary: This article introduces a method called TRIAGE-Cluster that utilizes genome-wide epigenetic data to identify genes that delineate cell diversity in scRNA-seq data. By integrating repressive chromatin patterns with weighted density estimation, TRIAGE-Cluster determines cell type clusters in a 2D UMAP space. The article also presents TRIAGE-ParseR, a machine learning method that evaluates gene expression rank lists to define gene groups governing the identity and function of cell types.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Biochemical Research Methods
Adam Gayoso, Zoe Steier, Romain Lopez, Jeffrey Regier, Kristopher L. Nazor, Aaron Streets, Nir Yosef
Summary: totalVI is a framework for end-to-end joint analysis of CITE-seq data which probabilistically represents data as a composite of biological and technical factors, providing a cohesive solution for common analysis tasks. It demonstrates strong performance in tasks such as dimensionality reduction, dataset integration, correlation estimation, and differential expression testing.
Article
Biochemical Research Methods
Roman Schefzik, Julian Flesch, Angela Goncalves
Summary: Researchers have developed and implemented a flexible and fast differential distribution testing procedure based on the 2-Wasserstein distance, which can detect any type of distribution difference between conditions. This method can also interpret distributional differences, capturing the relative contribution of changes in mean, variance, and shape under different conditions, and can be applied to a wide range of disciplines beyond scRNA-seq or bioinformatics.
Article
Biochemical Research Methods
Felicia S. L. Ng, David Ruau, Lorenz Wernisch, Berthold Gottgens
BRIEFINGS IN BIOINFORMATICS
(2018)
Article
Multidisciplinary Sciences
Serena Belluschi, Emily F. Calderbank, Valerio Ciaurro, Blanca Pijuan-Sala, Antonella Santoro, Nicole Mende, Evangelia Diamanti, Kendig Yen Chi Sham, Xiaonan Wang, Winnie W. Y. Lau, Wajid Jawaid, Berthold Gottgens, Elisa Laurenti
NATURE COMMUNICATIONS
(2018)
Review
Hematology
Sam Watcham, Iwo Kucinski, Berthold Gottgens
Article
Cardiac & Cardiovascular Systems
Viktoria Kalna, Youwen Yang, Claire R. Peghaire, Karen Frudd, Rebecca Hannah, Aarti Shah, Lourdes Osuna Almagro, Joseph J. Boyle, Berthold Gottgens, Jorge Ferrer, Anna M. Randi, Graeme M. Birdsey
CIRCULATION RESEARCH
(2019)
Article
Biochemistry & Molecular Biology
Julio Sainz de Aja, Sergio Menchero, Isabel Rollan, Antonio Barral, Maria Tiana, Wajid Jawaid, Itziar Cossio, Alba Alvarez, Gonzalo Carreno-Tarragona, Claudio Badia-Careaga, Jennifer Nichols, Berthold Gottgens, Joan Isern, Miguel Manzanares
Article
Hematology
Clara Bueno, Fernando J. Calero-Nieto, Xiaonan Wang, Rafael Valdes-Mas, Francisco Gutierrez-Aguera, Heleia Roca-Ho, Veronica Ayllon, Pedro J. Real, David Arambilet, Lluis Espinosa, Raul Torres-Ruiz, Antonio Agraz-Doblas, Ignacio Varela, Jasper de Boer, Anna Bigas, Bertie Gottgens, Rolf Marschalek, Pablo Menendez
Article
Multidisciplinary Sciences
Blanca Pijuan-Sala, Jonathan A. Griffiths, Carolina Guibentif, Tom W. Hiscock, Wajid Jawaid, Fernando J. Calero-Nieto, Carla Mulas, Ximena Ibarra-Soria, Richard C. V. Tyser, Debbie Lee Lian Ho, Wolf Reik, Shankar Srinivas, Benjamin D. Simons, Jennifer Nichols, John C. Marioni, Berthold Gottgens
Article
Biology
Antonio Barral, Isabel Rollan, Hector Sanchez-Iranzo, Wajid Jawaid, Claudio Badia-Careaga, Sergio Menchero, Manuel J. Gomez, Carlos Torroja, Fatima Sanchez-Cabo, Berthold Gottgens, Miguel Manzanares, Julio Sainz de Aja
Review
Multidisciplinary Sciences
Jong-Eun Park, Laura Jardine, Berthold Gottgens, Sarah A. Teichmann, Muzlifah Haniffa
Article
Cell Biology
Luke T. G. Harland, Claire S. Simon, Anna D. Senft, Ita Costello, Lucas Greder, Ivan Imaz-Rosshandler, Berthold Gottgens, John C. Marioni, Elizabeth K. Bikoff, Catherine Porcher, Marella F. T. R. de Bruijn, Elizabeth J. Robertson
Summary: The study shows that the T-box transcription factor Eomes influences chromatin accessibility at SCL-bound enhancers in the extra-embryonic mesoderm, regulating erythropoiesis and Runx1 expression. Eomes governs the haemogenic competency of ExM and is essential for the normal development of haemogenic endothelium. The findings suggest that haemogenic competence is established earlier during embryonic development than previously thought, with Eomes playing a crucial role in the transcriptional hierarchy of early blood formation.
NATURE CELL BIOLOGY
(2021)
Article
Oncology
Xiaonan Wang, Carlotta Peticone, Ekaterini Kotsopoulou, Berthold Gottgens, Fernando J. Calero-Nieto
Summary: This study used single-cell transcriptomic analysis to characterize the molecular features of CAR T cell activation, revealing several subpopulations of cells in CAR products with reproducible cellular composition across donors. Targeted data interrogation also showed that a small proportion of antigen-responding CAR-expressing cells exhibited exhaustion signatures with known markers and previously unassociated genes.
Correction
Cell Biology
Luke T. G. Harland, Claire S. Simon, Anna D. Senft, Ita Costello, Lucas Greder, Ivan Imaz-Rosshandler, Berthold Gottgens, John C. Marioni, Elizabeth K. Bikoff, Catherine Porcher, Marella F. T. R. de Bruijn, Elizabeth J. Robertson
NATURE CELL BIOLOGY
(2021)
Article
Multidisciplinary Sciences
Daniel Prins, Hyun Jung Park, Sam Watcham, Juan Li, Michele Vacca, Hugo P. Bastos, Alexander Gerbaulet, Antonio Vidal-Puig, Berthold Gottgens, Anthony R. Green
Article
Biochemistry & Molecular Biology
Iwo Kucinski, Nicola K. Wilson, Rebecca Hannah, Sarah J. Kinston, Pierre Cauchy, Aurelie Lenaerts, Rudolf Grosschedl, Berthold Goettgens
Article
Biotechnology & Applied Microbiology
F. Alexander Wolf, Fiona K. Hamey, Mireya Plass, Jordi Solana, Joakim S. Dahlin, Berthold Gottgens, Nikolaus Rajewsky, Lukas Simon, Fabian J. Theis