- General info
- Content
- Intended Learning Outcome
- Instructors
- Time and place
- Laptop
- Course material
- Program
-
- Monday - Introduction to population genetics and NGS data
- Tuesday - Inference of demographic history and population structure
- Wednesday - Advanced TWAS and introduction to single cell and spatial transcriptomics
- Thursday - Haplotype imputation and genome-wide association
- Friday – Mendelian randomization and introduction to transcriptome-wide association
- Evaluation
General info
Date November 6th to November 10th, 2023
Place BGI Headquarter in Dameisha, China National GeneBank, Shenzhen, China
Organized by University of Copenhagen, hosted by BGI college, with addional instructors from Aarhus University and Sun Yat-Sen University.
Price Free for all PhD students at Danish universities and BGI college. 200 Euro for all other students.
Includes Teaching. Food and accommodation are NOT included in the course fee.
Sign up registration form
Contact cphsummercourse@gmail.com
Content
Topics include
- introduction to high throughput sequencing (HTS) data
- Analysis of HTS data beyond mapping and variant calling
- Analysis of low depth HTS data including large scale imputation
- Population genetics and medical genomics analysis from HTS data
- Haplotype imputation for large data set
- GWAS studies from HTS data
- Mendelian randomization
- Computational approaches for transcriptomics
- Single Cell and spartial RNA sequencing
Intended Learning Outcome
After the course, the students should be able to:
- understand the problems with genotype calling based of aligning reads to a reference genome in different settings including ordinary DNA, ancient DNA and DNA from environmental samples
- select the proper analysis strategy given the data and the sciencetific questions
- understand the principal statistical framework to recover the variation from sequencing data and the limitations
- be able to properly interpret the variants from a probabilistic point of view
- use population genetic theory to infer basic population genetics characteristics from genetic data
- be able to infer ancestry and population structure based on genetic data
- use HTS data including low depth for population genetic inference
- understand how genetic can be used for causal inference
- quantify transcription and identify eQTLs
- be able to analyse single cell RNA
Teaching and learning methods
The main approach will be a mix of short lectures and exercises. Besides class-room sessions, there will be relevant research talks and practical individual and group exercises during the course to enhance the students’ comprehensions and applications of the bioinformatics approaches.
Instructors
Siyang Liu
Associate Professor at the School of Public Health (Shenzhen), Sun Yat-sen University. I am a computational biologist with a strong passion in applying sequencing technology and computational methodologies for variant detection, disease gene mapping and inference of population genetic history. I received my master and PhD training in the Bioinformatics Center of University of Copenhagen from 2012 to 2017. I have been a senior research scientist at BGI-shenzhen Life Science Institute since 2018 and I joined Sun Yat-sen University in 2021. My recent research endeavors predominantly focus on resolving methods for medical data mining, probabilistic modeling and data visualization within the realm of human statistical genetics and bioinformatics.
Anders Albrechtsen
Pofessor at the University of Copenhagen working with statistical models for applied population and medical genetics. I have a very interdisciplinary education with a PhD from the department of biostatistics, a masters from the bioinformatics center and a bachelor from molecular biology. In addition I have spent two years studying mathematics and spend more than a year working with disease mapping and Steno diabetes center. Doing my PhD and post docs I spent a couples of years at UC berkeley in the US and a few months at decode genetics in Iceland. My main focus for the last few years is developing method for HTS data, especially low depth data, and large scale association mapping studies based on both microarrays and HTS data.
Huanhuan Zhu
Malthe Sebro Rasmussen
Yonglun Luo
Time and place
The course will take place from November 6 to November 10 2023 at the BGI New Headquarter in Dameisha, Time and Space Center, Shenzhen, China
Laptop
You should bring a laptop to the course. We will log into a remove server from the laptop so any laptop will do regardless of operating system.
Course material
The lecture will be based on a large amount of reading material (articles/notes) that should be read in advance - you can find them here once they are finalized (you will get an email with password). The slides used during the lectures will be made available right before the lectures.
Program
We will have a morning and an afternoon session each day. Some of the days we will also have tours of some of the labs at BGI including their single cell sequencing facility
Monday - Introduction to population genetics and NGS data
- 09:00 - 09:15 Welcome and introduction (Anders Albrechtsen)
- 09:20 - 10:20 Lecture 1: Introduction to HTS I: format, genotype likelihoods and basic terms (Anders Albrechtsen)
- 10:30 - 12:00 Computer exercises I
- 12:00 - 01:00 Lunch
- 01:00 - 02:15 Lecture 2: Introduction to HTS II: ML estimators, EM algorithm and population structure (Malthe Sebro Rasmussen)
- 02:30 - 03:50 Computer exercises II
- 04:00 - ? Social outing
Tuesday - Inference of demographic history and population structure
- 09:00 - 10:15 Lecture 3: Popgen I: Population structure and PCA for low depth sequencing (Anders Albrechtsen)
- 10:30 - 12:00 Computer exercises III
- 12:00 - 01:00 Lunch
- 01:00 - 01:50 BGI-shenzhen tour of labs
- 02:00 - 03:15 Lecture 4: Popgen II: Inferernce of selection and demography (Rasmus Heller)
- 03:30 - 05:00 Computer exercises IV
Wednesday - Advanced TWAS and introduction to single cell and spatial transcriptomics
- 09:00 - 10:15 Lecture 5: Quantifying isoforms (Yonglun Luo)
- 10:30 - 12:00 Computer exercises V
- 12:00 - 01:00 Lunch (on your own)
- 01:00 - 02:15 Lecture 6: Introduction to single cell and spatial transcriptomics (Yonglun Luo)
- 02:30 - 04:00 Computer exercises VI
Thursday - Haplotype imputation and genome-wide association
- 09:00 - 10:15 Lecture 7: Haplotype imputation and phasing algorithms (Siyang Liu)
- 10:30 - 12:00 Computer exercises VII
- 12:00 - 01:00 Lunch (on your own)
- 01:00 - 02:50 Tour to China National Gene Bank
- 03:00 - 04:15 Lecture 8: GWAS and heritability estimation (Siyang Liu)
- 04:30 - 06:00 Computer exercises VIII
Friday – Mendelian randomization and introduction to transcriptome-wide association
- 09:00 - 10:15 Lecture 9: Mendelian randomization (Huanhuan Zhu)
- 10:30 - 12:00 Computer exercises IX
- 12:00 - 01:00 Lunch (on your own)
- 01:00 - 02:15 Lecture 10: Introduction to transcriptome-wide association (Huanhuan Zhu)
- 02:30 - 05:00 Computer exercises X
Evaluation
Participants who have participated actively in all parts of the course and completed all exercises satisfactorily will be awarded a certificate of completion at the end of the course. The work load corresponds to 5 ECTS points. Note that this workload includes one week of preparation. Reading material for this is available in the above course program.