Single Cell Seq Data Analysis Boot Camp


The course will provide a full single-cell RNA-sequencing (scRNA-seq) data analysis pipeline, starting from raw data up to the identification of trajectories / cell types, and corresponding (marker) genes associated with the biological structure in the data. Participants can expect a mix between background theory as taught through slides and hands-on lab sessions where real scRNA-seq data will be analyzed. The course will focus on tools and methods implemented within the R / Bioconductor environment.

This course is part of a larger course series in Data Analysis consisting op 19 individual modules. Find more information and enroll for this module via

  1. Overview of the course
  2. Introduction to single-cell RNA-seq technology: concepts and protocols of bulk and single-cell RNA sequencing; RNA-seq data characteristics; research questions that can be assessed using bulk and single-cell RNA-sequencing.
  3. Preprocessing and quality control of scRNA-seq data: Processing raw FASTQ-files (demultiplexing, mapping, barcode identification); quality control (low-quality/dead cells, doublets, empty droplets); The Bioconductor infrastructure for the analysis of scRNA-seq data; Normalization of scRNA-seq data.
  4. Dimensionality reduction, clustering and cell type identification: The curse of dimensionality; linear and non-linear dimensionality reduction methods; unsupervised cell type identification through clustering; (semi-)supervised cell type identification.
  5. Dataset integration and batch correction.
  6. Trajectory inference: dimensionality reduction for trajectory inference; trajectory inference concepts; RNA velocity.
  7. Differential expression between cell types, patients, and across/between trajectories.

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Single Cell Seq Data Analysis Boot Camp

  • Type of course: This is an on campus course.
  • Dates & times: November 17 and 24, December 1, 8 and 15, 2021, from 5.30 pm to 9.30 pm
  • Venue: UGent, Faculty of Sciences, Campus Sterre, Krijgslaan 281, building S9, 9000 Gent
  • Target audience: This course is aimed at biologists, bioinformaticians and statisticians interested in analysing single-cell RNA-seq datasets.
  • Exam/certificate: There is no exam connected to this course. Participants who attend all classes receive a certificate of attendance via e-mail at the end of the course.
  • Course prerequisites: Basic knowledge of R programming and statistics is assumed as provided in Module1 'Getting Started with R Software for Data Analysis' and Module 2 'Drawing Conclusions from Data: an Introduction' of this year's program.
  • Funding: => Our academy is recognised as a service provider for the 'KMO-portefeuille'. In this way small and middle sized businesses located in the Flanders region can save up to 30% on the registration fee for our courses. You can request this subsidy via up until 14 calender days after the course has started. => UGent PhD students can apply for a full refund from their Doctoral School.
  • Reduction: => If two or more employees from the same company enrol simultaneously for this course a reduction of 20% on the module price is taken into account starting from the second enrolment => Reduced prices apply to coworkers in governmental institutions, non-profit organisations and higher eduction as well as for students and the unemployed.
  • Enrolling for this course is possible via the IPVW-ICES website.