Article
Biotechnology & Applied Microbiology
Emma Dann, Neil C. Henderson, Sarah A. Teichmann, Michael D. Morgan, John C. Marioni
Summary: Milo is a scalable statistical framework that performs differential abundance testing by assigning cells to partially overlapping neighborhoods on a k-nearest neighbor graph. It can identify perturbations obscured by discretizing cells into clusters and outperforms alternative testing strategies. Milo is based on cell-cell similarity structure and may be applicable to various single-cell data beyond scRNA-seq.
NATURE BIOTECHNOLOGY
(2022)
Article
Multidisciplinary Sciences
Yingtian Hu, Glen A. Satten, Yi-Juan Hu
Summary: Compositional analysis is a robust method for analyzing microbiome data, and the proposed logistic regression approach, LOCOM, effectively handles experimental biases and shows improved sensitivity over existing methods.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Review
Biochemistry & Molecular Biology
Zhengyan Huang, Chi Wang
Summary: This review provides an overview of statistical methods for differential abundance (DA) analysis in mass spectrometry-based metabolomic data. The high-throughput data produced by mass spectrometry often contain a large fraction of zero values, and various statistical methods have been developed to characterize and analyze this zero-inflated data. The article discusses and compares different DA analysis methods in terms of their assumptions and statistical modeling techniques.
Article
Biochemical Research Methods
Reto Gerber, Mark D. Robinson
Summary: Innovations in single cell technologies have led to a surge in datasets and computational tools, but analyzing censored covariates remains a challenge. Research shows that multiple imputation based methods perform comparably to classical survival analysis methods while offering more flexibility in differential analysis.
BMC BIOINFORMATICS
(2021)
Article
Multidisciplinary Sciences
Alok K. Maity, Andrew E. Teschendorff
Summary: This study introduces a differential abundance testing paradigm called ELVAR, which uses cell attribute aware clustering to infer differentially enriched communities within the single-cell manifold. By benchmarking ELVAR against other algorithms using simulated and real datasets, the authors demonstrate that ELVAR improves the sensitivity to detect cell-type composition shifts in relation to aging, precancerous states, and Covid-19 phenotypes. Leveraging cell attribute information helps denoise single-cell data, avoid batch correction, and retrieve more robust cell states for subsequent differential abundance testing.
NATURE COMMUNICATIONS
(2023)
Article
Multidisciplinary Sciences
Kaiwen Wang, Yuqiu Yang, Fangjiang Wu, Bing Song, Xinlei Wang, Tao Wang
Summary: While scRNA-seq data analysis techniques are advanced, research on CyTOF data analysis has lagged behind. Dimension reduction methods were benchmarked on real and synthetic CyTOF samples, highlighting the high level of complementarity between the methods. The study provides useful guidelines for choosing the appropriate method based on data structure and analytical needs.
NATURE COMMUNICATIONS
(2023)
Article
Multidisciplinary Sciences
Shobana Stassen, Gwinky G. K. Yip, Kenneth K. Y. Wong, Joshua W. K. Ho, Kevin K. Tsia
Summary: Scalable trajectory inference for multi-omic single cell datasets is challenging due to the complexity of topologies. The VIA method presented in this study overcomes these limitations by using lazy-teleporting random walks to accurately reconstruct complex cellular trajectories.
NATURE COMMUNICATIONS
(2021)
Article
Biochemical Research Methods
Matteo Calgaro, Chiara Romualdi, Davide Risso, Nicola Vitulo
Summary: This article presents benchdamic, a Bioconductor package for benchmarking methods for the identification of differentially abundant taxa.
Article
Biochemical Research Methods
Eric Lee, Kevin Chern, Michael Nissen, Xuehai Wang, I. M. A. X. T. Consortium IMAXT Consortium, Chris Huang, Anita K. Gandhi, Alexandre Bouchard-Cote, Andrew P. Weng, Andrew Roth
Summary: Recent advances in spatial proteomics technologies have allowed for the profiling of multiple proteins in single cells, creating the opportunity to explore spatial relationships between cells. However, current clustering methods do not consider spatial context or prior knowledge about cell populations. In response, the authors developed SpatialSort, a Bayesian clustering approach that incorporates spatial awareness and prior biological knowledge to improve clustering accuracy and perform automated annotation.
Article
Statistics & Probability
Barak Brill, Amnon Amir, Ruth Heller
Summary: Identifying the microbiota taxa associated with traits of interest is crucial for advancing science and health. However, this task is challenging due to the compositional nature of the taxa counts and the sparsity of the data. This study focuses on Crohn's disease and shows that existing methods may produce a high number of false positives when identifying differentially abundant taxa. A novel nonparametric approach is introduced, which provides valid inference even with a substantial fraction of zero counts.
ANNALS OF APPLIED STATISTICS
(2022)
Review
Biochemical Research Methods
Lu Yang, Jun Chen
Summary: Differential abundance analysis (DAA) is a crucial statistical task in microbiome data analysis, and a robust DAA tool is important for identifying reliable microbial candidates. However, different DAA tools for correlated microbiome data (DAA-c) often yield inconsistent results. To address this issue, we conducted a comprehensive evaluation of existing DAA-c tools using real data-based simulations. Our findings indicate that linear model-based methods such as LinDA, MaAsLin2, and LDM are more robust than generalized linear models. Among them, LinDA method performs reasonably well even in the presence of strong compositional effects.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biochemical Research Methods
Shulei Wang
Summary: In this study, a new differential abundance test called the MsRDB test is proposed, which embeds the sequences into a metric space and integrates a multiscale adaptive strategy to identify differentially abundant microbes. Compared with existing methods, the MsRDB test can detect differentially abundant microbes at the finest resolution offered by data and is robust to zero counts, compositional effect, and experimental bias in the microbial compositional dataset.
Article
Biology
James W. Opzoomer, Jessica A. Timms, Kevin Blighe, Thanos P. Mourikis, Nicolas Chapuis, Richard Bekoe, Sedigeh Kareemaghay, Paola Nocerino, Benedetta Apollonio, Alan G. Ramsay, Mahvash Tavassoli, Claire Harrison, Francesca Ciccarelli, Peter Parker, Michaela Fontenay, Paul R. Barber, James N. Arnold, Shahram Kordasti
Summary: High-dimensional cytometry is an innovative tool for immune monitoring in health and disease, but analyzing large multiparametric datasets typically requires specialist computational knowledge. ImmunoCluster is an R package designed to aid nonspecialists in immune profiling cellular heterogeneity, providing scalable analysis and visualization tools tailored to users' needs. The framework consists of three core computational stages within an R-based open-source framework.
Article
Medicine, Research & Experimental
Dimitrios N. Sidiropoulos, Genevieve L. Stein-O'Brien, Ludmila Danilova, Nicole E. Gross, Soren Charmsaz, Stephanie Xavier, James Leatherman, Hao Wang, Mark Yarchoan, Elizabeth M. Jaffee, Elana J. Fertig, Won Jin Ho
Summary: Mass cytometry, or CyTOF, can be used to determine protein-level measurements of more than 40 markers simultaneously. In this study, single-cell trajectory inference and nonnegative matrix factorization methods were applied to CyTOF data to track the dynamics of T cell states. The continuous phenotypic shifts in T cells could be inferred from CyTOF data, and transfer learning enabled estimation of patient-specific cell states in new sample cohorts.
Article
Biochemical Research Methods
Lis Arend, Judith Bernett, Quirin Manz, Melissa Klug, Olga Lazareva, Jan Baumbach, Dario Bongiovanni, Markus List
Summary: Cytometry techniques are widely used for discovering cellular characteristics at single-cell resolution. This study systematically evaluated existing and novel approaches for differential expression analysis on real and simulated CyTOF data. A new method, CyEMD, was proposed to handle strong zero-inflation without being too sensitive. Additionally, a user-friendly R Shiny App tool called CYANUS was developed for cytometry data analysis.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Cell Biology
Carolina Guibentif, Jonathan A. Griffiths, Ivan Imaz-Rosshandler, Shila Ghazanfar, Jennifer Nichols, Valerie Wilson, Berthold Gottgens, John C. Marioni
Summary: Somite formation is essential for the development of vertebrate body plan, involving three transcriptional trajectories in the early mouse embryo. Anterior somites ingress through the primitive streak before E7, while neuromesodermal progenitors are reserved for later somitogenesis. The role of T in somite development and the potential regulators of early T-independent somites are investigated, challenging the T-Sox2 antagonism model in early NMPs.
DEVELOPMENTAL CELL
(2021)
Article
Biochemistry & Molecular Biology
Emily Stephenson, Gary Reynolds, Rachel A. Botting, Fernando J. Calero-Nieto, Michael D. Morgan, Zewen Kelvin Tuong, Karsten Bach, Waradon Sungnak, Kaylee B. Worlock, Masahiro Yoshida, Natsuhiko Kumasaka, Katarzyna Kania, Justin Engelbert, Bayan Olabi, Jarmila Stremenova Spegarova, Nicola K. Wilson, Nicole Mende, Laura Jardine, Louis C. S. Gardner, Issac Goh, Dave Horsfall, Jim McGrath, Simone Webb, Michael W. Mather, Rik G. H. Lindeboom, Emma Dann, Ni Huang, Krzysztof Polanski, Elena Prigmore, Florian Gothe, Jonathan Scott, Rebecca P. Payne, Kenneth F. Baker, Aidan T. Hanrath, Ina C. D. Schim van der Loeff, Andrew S. Barr, Amada Sanchez-Gonzalez, Laura Bergamaschi, Federica Mescia, Josephine L. Barnes, Eliz Kilich, Angus de Wilton, Anita Saigal, Aarash Saleh, Sam M. Janes, Claire M. Smith, Nusayhah Gopee, Caroline Wilson, Paul Coupland, Jonathan M. Coxhead, Vladimir Yu Kiselev, Stijn van Dongen, Jaume Bacardit, Hamish W. King, Anthony J. Rostron, A. John Simpson, Sophie Hambleton, Elisa Laurenti, Paul A. Lyons, Kerstin B. Meyer, Marko Z. Nikolic, Christopher J. A. Duncan, Kenneth G. C. Smith, Sarah A. Teichmann, Menna R. Clatworthy, John C. Marioni, Berthold Gottgens, Muzlifah Haniffa
Summary: Transcriptomic and proteomic profiling of blood samples from individuals with COVID-19 reveals immune cell and hematopoietic progenitor cell alterations that are differentially associated with disease severity.
Article
Multidisciplinary Sciences
Liora Haim-Vilmovsky, Johan Henriksson, Jennifer A. Walker, Zhichao Miao, Eviatar Natan, Gozde Kar, Simon Clare, Jillian L. Barlow, Evelina Charidemou, Lira Mamanova, Xi Chen, Valentina Proserpio, Jhuma Pramanik, Steven Woodhouse, Anna V. Protasio, Mirjana Efremova, Julian L. Griffin, Matt Berriman, Gordon Dougan, Jasmin Fisher, John C. Marioni, Andrew N. J. McKenzie, Sarah A. Teichmann
Summary: The transcription factor Rora plays a crucial role in the development of ILC2, ILC3, macrophages, and Treg cells, and its function in CD4+ T cells has been investigated. Rora appears to act as a negative regulator of the immune system through various downstream pathways, potentially influenced by the local microenvironment.
Article
Multidisciplinary Sciences
Muzlifah Haniffa, Deanne Taylor, Sten Linnarsson, Bruce J. Aronow, Gary D. Bader, Roger A. Barker, Pablo G. Camara, J. Gray Camp, Alain Chedotal, Andrew Copp, Heather C. Etchevers, Paolo Giacobini, Berthold Gottgens, Guoji Guo, Ania Hupalowska, Kylie R. James, Emily Kirby, Arnold Kriegstein, Joakim Lundeberg, John C. Marioni, Kerstin B. Meyer, Kathy K. Niakan, Mats Nilsson, Bayanne Olabi, Dana Pe'er, Aviv Regev, Jennifer Rood, Orit Rozenblatt-Rosen, Rahul Satija, Sarah A. Teichmann, Barbara Treutlein, Roser Vento-Tormo, Simone Webb
Summary: The Human Developmental Cell Atlas initiative aims to create a comprehensive reference map of cells during development to understand the basis of human development, congenital and childhood disorders, as well as aging, cancer, and regenerative medicine. The initiative integrates scientists’ data on human development and uses state-of-the-art technologies to create a reference atlas across gestation.
Article
Biotechnology & Applied Microbiology
T. Lohoff, S. Ghazanfar, A. Missarova, N. Koulena, N. Pierson, J. A. Griffiths, E. S. Bardot, C. -H. L. Eng, R. C. V. Tyser, R. Argelaguet, C. Guibentif, S. Srinivas, J. Briscoe, B. D. Simons, A. -K. Hadjantonakis, B. Gottgens, W. Reik, J. Nichols, L. Cai, J. C. Marioni
Summary: Improved integration of spatial and single-cell transcriptomic data through the seqFISH method provides insights into mouse development, revealing cell types across the embryo and uncovering axes of cell differentiation that are not apparent from scRNA-seq data. This approach offers a high-resolution spatial map for studying cell fate decisions in complex tissues and development.
NATURE BIOTECHNOLOGY
(2022)
Article
Multidisciplinary Sciences
Karol Nowicki-Osuch, Lizhe Zhuang, Sriganesh Jammula, Christopher W. Bleaney, Krishnaa T. Mahbubani, Ginny Devonshire, Annalise Katz-Summercorn, Nils Eling, Anna Wilbrey-Clark, Elo Madissoon, John Gamble, Massimiliano Di Pietro, Maria O'Donovan, Kerstin B. Meyer, Kourosh Saeb-Parsy, Andrew D. Sharrocks, Sarah A. Teichmann, John C. Marioni, Rebecca C. Fitzgerald
Summary: This study revealed that Barrett's esophagus originates from the gastric cardia through specific transcriptional programs. Esophageal adenocarcinoma likely arises from undifferentiated Barrett's esophagus cell types, even in the absence of a clearly identifiable metaplastic precursor. This finding has important implications for early cancer detection strategies.
Article
Biotechnology & Applied Microbiology
Emma Dann, Neil C. Henderson, Sarah A. Teichmann, Michael D. Morgan, John C. Marioni
Summary: Milo is a scalable statistical framework that performs differential abundance testing by assigning cells to partially overlapping neighborhoods on a k-nearest neighbor graph. It can identify perturbations obscured by discretizing cells into clusters and outperforms alternative testing strategies. Milo is based on cell-cell similarity structure and may be applicable to various single-cell data beyond scRNA-seq.
NATURE BIOTECHNOLOGY
(2022)
Article
Biotechnology & Applied Microbiology
Rebecca Berrens, Andrian Yang, Christopher E. Laumer, Aaron T. L. Lun, Florian Bieberich, Cheuk-Ting Law, Guocheng Lan, Maria Imaz, Joseph S. Bowness, Neil Brockdorff, Daniel J. Gaffney, John C. Marioni
Summary: CELLO-seq enables mapping of transposable element expression to unique genomic loci. Utilizing this technique, widespread TE expression was observed in two-cell mouse blastomeres and human induced pluripotent stem cells. Simulations showed that only a small number of very young elements in the mouse could not be confidently mapped back to the reference genome. Heterogeneity in the relationship between the expression of individual elements and putative regulators was revealed, indicating distinct regulatory mechanisms for different TE classes.
NATURE BIOTECHNOLOGY
(2022)
Article
Biochemical Research Methods
Dario Righelli, Lukas M. Weber, Helena L. Crowell, Brenda Pardo, Leonardo Collado-Torres, Shila Ghazanfar, Aaron T. L. Lun, Stephanie C. Hicks, Davide Risso
Summary: SpatialExperiment is a new data infrastructure for storing and accessing spatially-resolved transcriptomics data, implemented in the R/Bioconductor framework. It offers advantages such as modularity, interoperability, standardized operations, and comprehensive documentation. The project provides example datasets and visualization tools for users.
Article
Cell Biology
Kelvin Yin, Daniel Patten, Sarah Gough, Susana de Barros Goncalves, Adelyne Chan, Ioana Olan, Liam Cassidy, Marta Poblocka, Haoran Zhu, Aaron Lun, Martijn Schuijs, Andrew Young, Celia Martinez-Jimenez, Timotheus Y. F. Halim, Shishir Shetty, Masashi Narita, Matthew Hoare
Summary: Senescence is a stress-responsive tumor suppressor mechanism associated with the expression of the senescence-associated secretory phenotype (SASP). Through SASP, senescent cells trigger their own immune-mediated elimination, which is prevented by the endothelium. This study demonstrates that SASP induces endothelial cell NF-kappa B activity and that this activity regulates immune cell recruitment and senescence surveillance. Furthermore, oncogenic hepatocyte senescence also influences endothelial NF-kappa B activity in vivo.
GENES & DEVELOPMENT
(2022)
Review
Immunology
Arianne C. Richard
Summary: The advent of technologies that can characterize individual cells has revealed extensive diversity between cells of the same subset, including CD8(+) T cells. This review focuses on heterogeneity in CD8(+) T cell responses, particularly the impact of TCR stimulation strength and the mechanisms underlying variation between cells.
FRONTIERS IN IMMUNOLOGY
(2022)
Article
Immunology
Philippa R. Barton, Alexander J. Davenport, Jens Hukelmann, Doreen A. Cantrell, Jane C. Stinchcombe, Arianne C. Richard, Gillian M. Griffiths
Summary: Bach2 is a transcriptional regulator that plays a major role in T cell-mediated immune regulation. In the absence of BACH2, effector CTLs derived from CD8(+) T cells show enhanced proliferative and cytolytic capacity. BACH2-deficient T cells have a higher abundance of memory cells and a reduced abundance of naive cells compared to wild-type T cells. Furthermore, BACH2-deficiency leads to the production of enlarged cytolytic granules, resulting in enhanced cytotoxicity in effector CTLs.
EUROPEAN JOURNAL OF IMMUNOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Arianne C. Richard, Claire Y. Ma, John C. Marioni, Gillian M. Griffiths
Summary: This study investigates the impact of transcriptomic changes on the killing ability of effector cytotoxic T lymphocytes (CTLs). The results show that while transcription is required for the expression of cytokines/chemokines and transcriptional machinery, it is relatively robust to transcription blockade for cytotoxic protein expression and cytolytic activity. Additionally, the study reveals a cell-intrinsic transcriptional requirement for infiltration.
Article
Genetics & Heredity
Emma Dann, Ana-Maria Cujba, Amanda J. Oliver, Kerstin B. Meyer, Sarah A. Teichmann, John C. Marioni
Summary: Joint analysis of diseased tissues and healthy reference data can reveal altered cell states. Using a reference atlas for latent space learning followed by differential analysis against controls improves identification of disease-associated cells, especially with multiple perturbed cell types. Reducing control sample numbers does not increase false discovery rates.
Article
Biotechnology & Applied Microbiology
Melania Barile, Ivan Imaz-Rosshandler, Isabella Inzani, Shila Ghazanfar, Jennifer Nichols, John C. Marioni, Carolina Guibentif, Berthold Gottgens
Summary: The study demonstrates that RNA velocity can accurately identify the starting point of epiblast cells, but trajectory predictions at later stages are inconsistent with real-time ordering and existing knowledge, especially in red blood cell maturation. Investigating the underlying causes reveals a coordinated step-change in gene transcription, which challenges current velocity analysis assumptions. The study highlights the importance of considering time-dependent changes in expression dynamics and uncovers implications for various differentiation processes.
