M3 - Single Cell Seq Data Analysis Boot Camp
Type of Course - Dates - Venue - Description - Target audience - Exam - IMPORTANT: Incorporation in DTP and reimbursement by DS
Course prerequisites - Teachers - Course material - Fees - Enrol
Type of course
This is an on campus course, with blended learning options.
Dates
November 17 and 24, December 1, 8 and 15, 2021, from 5.30 pm to 9.30 pm
Please note: the deadline for UGent PhD students who want a refund to open a dossier on the DS website (Application for Registration) is October 15, 2021.
Venue
Campus Sterre, Krijgslaan 281, 9000 Ghent, pc room 1.1 - A. Turing
Description
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. The detailed schedule includes:
- Overview of the course
- 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.
- 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.
- 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.
- Dataset integration and batch correction.
- Trajectory inference: dimensionality reduction for trajectory inference; trajectory inference concepts; RNA velocity.
- Differential expression between cell types, patients, and across/between trajectories.
Target audience
This course is aimed at biologists, bioinformaticians and statisticians interested in analysing single-cell RNA-seq datasets.
Exam
There is no exam connected to this module. Participants receive a certificate of attendance via e-mail at the end of the course.
Incorporation in DTP and reimbursement from DS for UGent PhD students
As a UGent PhD student, to be able to incorporate this 'specialist course' in your Doctoral Training Program (DTP) and get a refund of the registration fee from your Doctoral School (DS) you need to follow strict rules: please take the necessary action in time. The deadline to open a dossier on the DS website (Application for Registration) for this course is October 15, 2021. Please note that opening a dossier does not mean that you are enrolled. You still need to enrol via the registration form on this site.
Course prerequisites
Basic knowledge of R programming and statistics is assumed as provided in Module 1 and Module 2 of this year's program.
Teacher
Course material
Slides and analysis scripts will be provided as an R Markdown file. Compiled results will be available on the course website.
Fees
A different price applies, depending on your main type of employment.
Employment | Module 3 |
---|---|
Industry/Private sector1 | 925 |
Non-profit, government, higher education staff2 | 695 |
(Doctoral)students, retired, unemployed2 | 310 |
1 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.
2 UGent staff and UGent doctoral students who pay internally via SAP or internal transfer can participate at these special prices.