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Statistical Analysis of High-Throughput Genomic and Transcriptomic Data

Fall/Herbst-semester 2020

Lectures

Mondays 9.00-9.45 (remote), 10.00-10.45 (remote)

Exercises

Monday 11.00-11.45 (remote)

Lecturers

Dr. Hubert Rehrauer, Group Leader of Genome Informatics at FGCZ

Prof. Dr. Mark Robinson, Associate Professor of Statistical Genomics, IMLS, UZH

Teaching Assistant

Ahmadreza Yousefkhani, M.Sc. student in Computational Biology and Bioinformatics

Schedule

Date Lecturer Topic Exercise JC1 JC2 Tutorial
14.09.2020 Mark + Hubert admin; mol. bio. basics R markdown; git(hub)
21.09.2020 Mark interactive technology/statistics session group exercise: technology pull request Exploratory data analysis and visualization with ggplot2 and dplyr
28.09.2020 Hubert NGS intro; exploratory data analysis EDA in R PCA - concept and pitfalls
05.10.2020 Hubert mapping Rsubread Linear regression, diagnostic plots and residual analysis
12.10.2020 Mark limma + friends linear model simulation + design matrices Linear regression, tests and confidence regions, F-value analysis
19.10.2020 Hubert RNA-seq quantification RSEM R-squared and model selection in linear models, Mallow Cp statistic, AIC, BIC criterion
26.10.2020 Mark edgeR+friends 1 basic edgeR/voom DUBStepR: correlation-based feature selection for clustering single-cell RNA sequencing data (TK, SS, TE) From expression footprints to causal pathways: contextualizing large signaling networks with CARNIVAL (DC, LM)
02.11.2020 Mark edgeR+friends 2 GLM/DEXSeq Redefining CpG islands using hidden Markov models (Zhiwei Dou, Huixin Jin, Peiying Cai) Causal Inference in Genetic Trio Studies (ZS, GW, LN)
09.11.2020 Kathi hands-on session #1: RNA-seq FASTQC/Salmon/etc. Statistical significance for genomewide studies (RA, HH, JR) Identifying signaling genes in spatial single cell expression data (YM, KD, GJ)
16.11.2020 Hubert single-cell 1: preprocessing, dim. reduction, clustering Testing hypotheses about the microbiome using the linear decomposition model (FS,BO,SA) Generalizing RNA velocity to transient cell states through dynamical modeling (DP, EH)
23.11.2020 Helena hands-on session #2: cytometry cytof null comparison Genome-wide detection of intervals of genetic heterogeneity associated with complex traits (Richard Affolter, Philip Hartout, Martin Emons) Empirical Bayes Analysis of a Microarray Experiment (Jennifer Probst, Eljas Röllin, Lisa Herzog)
30.11.2020 Mark single-cell 2: cell type definition, differential state scRNA exercise 2 A Bayesian mixture model for the analysis of allelic expression in single cells (Sneha-Sundar,SmaragdaDimitrakopoulou,marinapanteli) scMET: Bayesian modelling of DNA methylation heterogeneity at single-cell resolution (MW, RM, DW)
07.12.2020 Pierre-Luc hands-on session #3: single-cell RNA-seq full scRNA-seq pipeline ScreenBEAM: a novel meta-analysis algorithm for functional genomics screens via Bayesian hierarchical modeling (Leonor Schubert, Jonathan Haab, Flavio Rump) Detection of differentially abundant cell subpopulations discriminates biological states in scRNA-seq data (TE, RB, AB)
14.12.2020 Mark loose ends: HMM, EM, robustness segmentation, peak finding NEBULA: a fast negative binomial mixed model for differential expression and co-expression analyses of large-scale multi-subject single-cell data (HML, SCD, SW) A test metric for assessing single-cell RNA-seq batch correction (Dimitri Schmid, Lola Kouroma, Jonas Bucher); AUC-RF: A New Strategy for Genomic Profiling with Random Forest (Jonas Meirer, Dominique Paul)

Course material

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/sta426hs2020/material.git

Alternatively, for a ZIP file of the repository, you can click on the (green) 'Clone or download' (top right) and then click 'Download ZIP'.

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