SCOG Virtual Lecture Series
03 July 2020: Julio Saez-Rodriguez (Heidelberg University): "Extracting mechanistic insight from single-cell and spatial transcriptomics"
Single-cell technologies generate large datasets that allow us to study biomedical processes with unprecedented detail. These data could, in principle, shed light on the cellular communication mechanisms that control homeostasis in multi-cellular systems, and how these mechanisms go wrong in diseases ranging from cancer to heart failure. We have developed a set of tools for the analysis transcriptomic data, ranging from a meta-resource of biological knowledge (Omnipath) to methods to infer pathway and transcription factor activities (PROGENy and DoRothEA, respectively) from gene expression and subsequently infer causal paths among them (CARNIVAL). We have recently adopted these tools to single-cell data, supported by a comprehensive benchmark with in silico and real data. We have also developed approaches to analyze transcriptomic data with spatial resolution. In particular, our method MISTy is a flexible, scalable, and explainable machine learning framework for extracting interactions from spatial omics data. MISTy builds multiple views focusing on different spatial or functional contexts to dissect different effects. We have also integrated the aforementioned to estimate the activities of pathways and transcription factors in MISTy, enabling us the analysis of intercellular signaling in a spatial context. All our methods are freely available as R-packages. I will illustrate these strategies in ongoing studies of with unpublished data in various disease contexts that we are performing with clinical collaborators.
Register for the Virtual Lecture Series here.
19 June 2020: Joachim L. Schultze (DZNE, Bonn): "Single Cell Omics on COVID-19 in DeCOI"
The current pandemic crisis triggered by SARS-CoV-2 leads to very different disease courses of COVID-19 ranging from very mild to very severe with multi-organ failure. A significant number of patients with severe symptoms even succumb the infection. The host’s cellular reaction seems to be of utmost importance and responsible for this heterogenous response to the virus. Clearly, single cell omics can significantly contribute to our understanding of cellular reactions of infected cells and the response of the immune cells towards the infected cells. Over the last weeks, the German COVID-19 OMICS Initiative was established to coordinate NGS-based research efforts in COVID-19 research in Germany and together with colleagues world-wide. I will present initial results from single cell omics studies that are conducted on patient samples derived from COVID-19 patients within DeCOI.
Register for the Virtual Lecture Series here.
SCOG Workshop Computational Single Cell Genomics, March 2019, Munich
Watch the workshop sessions following the links. Thanks to the Chan Zuckerberg Initiative for sponsoring the recordings.
|Christoph Bock||CeMM Research Center, Vienna||CRISPR single-cell sequencing: Toward functional biology in high throughput|
|Joachim Schultze||DZNE, Bonn||From single cells to patients: A LifeTime journey|
|Sam Riesenfeld||Broad Institute of MIT and Harvard, Boston||Using topic models to analyze the transcriptional spectrum of innate lymphoid cells|
|Clément Cochain||Comprehensive Heart Failure Center, Würzburg||Time series single-cell analysis of cardiac myeloid cells after acute myocardial infarction in mice|
|Heiko Lickert||Helmholtz Munich||Deciphering mechanisms of β-cell failure and regeneration by single cell RNA Sequencing|
|Peter Kharchenko||Harvard Medical School, Boston||Wiring together large single-cell RNA-seq collections|
|Vahid Shahrezaei||Imperial College London||Bayesian gene expression recovery, imputation and normalisation for single cell RNA-sequencing data|
|Amit Frishberg||Tel Aviv University||Cell composition analysis of bulk genomics using single-cell data|
|David Fischer||Helmholtz Munich||diffxpy: Scalable differential expression analysis for single-cell RNA-seq data|
|Angela Goncalves||DKFZ Heidelberg||Determining KIR repertoires using single cell transcriptomics|
|Maria Colomé-Tatché||Helmholtz Munich||Episcanpy: epigenomic single cell analysis|
|Sara Aibar||VIB-KU Leuven||Exploiting single-cell transcriptomics and epigenomics to reconstruct gene-regulatory networks|
Helmholtz Horizons 2018
The Helmholtz Horizons Symposium 2018, hosted by the President of the Association, highlights scientific breakthroughs of Helmholtz’s established researchers, showcases talented early career researchers, and gives a platform to the entrepreneurs and innovators, who ensure that Helmholtz research has societal impact.
Visit the Helmholtz Horizons Website.
Video production: BIOCOM
Fabian Theis: ‘The Digital (R)Evolution in Science’ – Berlin, 2018 talking about ‘Learning cell lineages using artificial intelligence’.
Christin Sünkel @ Helmholtz Horizons 2018: ‘The Digital (R)Evolution in Science’ – Berlin, 2018
“Single Cells in Time and Space”
Single cell RNA sequencing allows us to study all genes that are being used in a single cell. However powerful this method is, it leaves us with thousands of data points for each cell and we study thousands of cells per experiment. Hence, there is a big need to develop computational methods that can deal with this kind of “big data”.
In her presentation Christin also introduces the LifeTime initiative for a new FET-Flagship which is coordinated by Nikolaus Rajewsky, Head of the Berlin Institute for Medical Systems Biology at the Max-Delbrück Center for Molecular Medicine.
Christin Sünkel studied biochemistry and molecular biology at the University of Bayreuth. As a student intern at the Rockefeller University in New York City, in the laboratory of Thomas Tuschl she worked on the role of certain RNA-binding proteins. Her studies were supported by the Studienstiftung des deutschen Volkes. For her master thesis she moved to the laboratory of Nikolaus Rajewsky at Max-Delbrück Center for Molecular Medicine / Berlin Institute for Medical Systems Biology in Berlin to develop in vitro methods for the study of circular RNAs. Now she is pursuing her PhD in Nikolaus Rajewsky’s lab focusing on the function of circular RNAs and on the development of a method to study single cell gene expression in a spatial context. Her PhD work is supported by the Boehringer Ingelheim Fonds, Signgene and MDC BOOST.
Single Cell Data Analysis - Overview
This video has been made for bioinformatics students in Cairo University, Egypt; to discuss the main Single Cell Data Analysis challenges.
Hemberg lab course: https://hemberg-lab.github.io/scRNA.seq.course/
Abdelrahman Mahmoud @ DKFZ – Heidelberg, 2018.