Course syllabus
Epigenomics Data Analysis: from Bulk to Single Cell
24 - 28 October 2022
Course Info
The aim of this workshop is to introduce best practice bioinformatics methods for processing, analyses and integration of epigenomics data. The online teaching includes lectures, programming tutorials and interactive group sessions. This workshop is run by the National Bioinformatics Infrastructure Sweden (NBIS).
Audience Course open to PhD students, postdocs, and other researchers. Note that priority is given to Swedish academia.
Fee This online training event has no fee. However, if you confirm your participation but do not do so (no-show) you will be invoiced 2000 SEK. Please note that NBIS cannot invoice individuals.
By accepting to participate in the course, you will be agreeing to follow the NBIS Training Code of Conduct.
Covered topics
This workshop is designed to introduce best practice bioinformatics methods for processing, analyses and integration of epigenomics and functional genomics data.
Topis covered include:
- Data processing and analyses for differential DNA methylation with Illumina EPIC arrays and Bisulfite-seq;
- ChIP-seq: peak calling, peak independent / dependent quality metrics, differential binding analysis; DNA motif enrichment;
- ATAC-seq: peak calling, peak independent / dependent quality metrics, differential accessibility analysis;
- Functional analysis, including finding nearest genes and custom features, GO terms and Reactome pathways enrichment;
- Quantitative ChIP-seq;
- CUT&Tag / CUT&RUN: Novel methods to investigate protein-chromatin interactions;
- Integrative visualisations of epigenomics datasets;
- Basic multi-omics exploration and integration;
- Introduction to analysis of single cell functional genomics data (scATAC-seq);
- Nf-cores pipelines: Methylseq, ChIP-seq, ATAC-seq
Application
This is a national course. The course is open for PhD students, postdocs, group leaders and core facility staff. NBIS prioritises academic participants, especially PhD students, affiliated with Swedish universities. We warmly welcome international and/or non-academic participants when we have seats available and the requirements criteria are met.
Please note that NBIS training events do not provide any formal university credits. The training content is estimated to correspond to a certain number of credits, however the estimated credits are just guidelines. If formal credits are crucial, the student needs to confer with the home department before submitting a course application in order to establish whether the course is valid for formal credits or not.
Entry requirements
Required to be able to follow the tutorials:
- BYOL, bring your own laptop with R and RStudio installed
- Basic knowledge in Linux
- Basic R programming experience
Makes learning experience easier:
- Experience working on the SNIC center Uppmax or another HPC
- Previous experience with NGS data analyses
- Completing NBIS workshops “Introduction to Bioinformatics using NGS data” and “R Programming Foundations for Life Scientists” or equivalent
Due to limited space the course can accommodate maximum of 30 participants. If we receive more applications, participants will be selected based on several criteria. Selection criteria include correct entry requirements, motivation to attend the course as well as gender and geographical balance.
Certificate & University credits
We will issue a course certificate upon a successful course completion, assessed by active participation in all course sessions (lectures, computer practicals, group discussion etc.).
Unfortunately we are not able to warrant any university credits (högskolepoäng). Many universities however, recognize the attendance in our courses and award 1.5 HPs, corresponding to a 40 h of studying. It is up to participants to clarify and arrange credit transfer with the relevant university department.
Schedule
The course schedule is not yet finalised. The course schedule edition 2022 can be found here.
Precourse material
Please read carefully the precourse materials prior to starting the course.
Teaching Team
Agata Smialowska, Jakub Orzechowski Westholm, Vincent van Hoef, Simon Elsässer, Jessica Nordlund
Image source: www.gene.com