Training : Single-Cell : Transcriptomics, Spatial and Multi-Omics (sincellTE)
Deadline pre-registration: 15th September 2021
This one-week class focuses on the large-scale study of heterogeneity across individual cells from the genomic, transcriptomic and epigenomic points of view. New 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 Student and Post Doc 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, cell phenotyping and additional multi-omics.
Requirements : Participants must have prior experience on NGS data analysis with everyday use of R and good knowledge of Unix command line. Before the training, participants will be asked to familiarize themselves with the processing and primary analyses steps of scRNA-seq datasets with provided pedagogic material.
It is not necessary to have personal single-cell data to analyse.
All information and pre-registration:
See also: Training Platform