Fall/Herbst-semester 2023
Mondays 9.00-9.45 (Y27-H-46), 10.00-10.45 (Y27-H-46)
Monday 11.00-11.45
Dr. Hubert Rehrauer, Group Leader of Genome Informatics at FGCZ
Prof. Dr. Mark Robinson, Professor of Statistical Genomics, DMLS, UZH
| Date | Lecturer | Topic | Exercise | JC1 | JC2 |
|---|---|---|---|---|---|
| 18.09.2023 | Mark + Hubert | admin; mol. bio. basics | quarto; git(hub) | ||
| 25.09.2023 | Mark | interactive technology/statistics session | group exercise: technology pull request | ||
| 02.10.2023 | Hubert | NGS intro; exploratory data analysis | EDA in R | ||
| 09.10.2023 | Mark | limma + friends | linear model simulation + design matrices | ||
| 16.10.2023 | Hubert | mapping | Rsubread | ||
| 23.10.2023 | Hubert | RNA-seq quantification | RSEM | SEACells infers transcriptional and epigenomic cellular states from single-cell genomics data (MB, HW) | X |
| 30.10.2023 | Mark | edgeR+friends 1 | basic edgeR/voom | Normalization of RNA-seq data using factor analysis (MR, RD) | X |
| 06.11.2023 | tba | hands-on session #1: RNA-seq | FASTQC/Salmon/etc. | Statistical significance for genomewide studies (DA, KS, FM) | Identification of cell types, states and programs by learning gene set representations (TO, MC, GC) |
| 13.11.2023 | Mark | edgeR+friends 2 | advanced edgeR/voom | OUTRIDER:A novel hierarchical clustering algorithm for gene sequences (AB, PB, CD) | Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics (DB, CB) |
| 20.11.2023 | Hubert | single-cell 1: preprocessing, dim. reduction, clustering | clustering | X | X |
| 27.11.2023 | tba | hands-on session #2: cytometry | cytof null comparison | SpatialDM for rapid identification of spatially co-expressed ligand–receptor and revealing cell–cell communication patterns (EG, AE) | Differential abundance testing on single-cell data using k-nearest neighbor graphs(CC, ZY, XY) |
| 04.12.2023 | Mark | single-cell 2: clustering, marker gene DE | marker gene DE | Redefining CpG islands using hidden Markov models (MI, MT, AT) | SPOTlight: seeded NMF regression to deconvolute spatial transcriptomics spots with single-cell transcriptomes (NG, ZZ) |
| 11.12.2023 | tba | hands-on session #3: single-cell RNA-seq (cell type definition, differential state) | full scRNA-seq pipeline | chromVAR: inferring transcription-factor-associated accessibility from single-cell epigenomic data (GP, ER, GB) | X |
| 18.12.2023 | Mark | spatial omics | spatial statistics | X | X |
Assuming you have git installed locally, you can check out the entire set of course materials with the following command (from command line):
git clone https://github.com/sta426hs2023/material.git
and get updates by running git pull at any later time in the same directory.
Alternatively, to retrieve a ZIP file of the repository, you can click on the (green) 'Code' button (top right of main panel) and then click 'Download ZIP'.