Dear all, Please find below the announcement for the 5th Workshop in single cell data analyses 2024 Best, Morgane ------------------------------------ Training : Single-Cell : Transcriptomics, Spatial and Long reads (sincellTE) Date : 20th October 2024 – 25th October 2024 Place : Roscoff, France Deadline pre-registration: 7th May 2024 This one-week class focuses on the large-scale study of heterogeneity across individual cells from a genomics and transcriptomics points of view. Recent technological developments enable the characterization of molecular information at a single cell resolution for large numbers of cells. The high dimensional omics data that these technologies produce comes with novel methodological challenges for the analysis. In this regard, specific bioinformatics and statistical methods have been developed in order to extract robust information. This course is directed towards engineers and researchers who regularly need to undertake single-cell data analysis as well as PhD students and postdoctoral fellows in computational biology or bioinformatics that are interested in the development of methods and pipelines for highly dimensional single-cell data analysis. A wide range of single cell topics will be covered in lectures, demonstrations and practical classes. Among others, the areas and issues to be addressed will include the choice of the most appropriate single-cell sequencing technology, the experimental design and the bioinformatics and statistical methods and pipelines. For this edition, new courses/practicals will focus on spatial transcriptomics, long reads, artificial intelligence and FAIR access to the data/code. Requirements : Participants must have prior experience on NGS data analysis with everyday use of R and/or Python and good knowledge of Unix command line. Before the training, participants are advised to familiarize themselves with the processing and primary analyses steps of scRNA-seq datasets. It is not necessary to have personal single-cell data to analyse. All information and pre-registration: https://moodle.france-bioinformatique.fr/course/view.php?id=27