Fall Workshop Series
Introduction
Please visit our iLab request page for current information on workshops. The fall workshop session is typically held in October.
NOTE. In order to register you will need a UIC iLab account. If you do not have one please visit https://rrc.uic.edu/get-started/user-registration/.
Workshop Sessions
The following workshops days are offered in this series. You may join any or all of the days that suit your skills needs.
R Essentials for Data Analysis
Learn the RStudio interface and programming language, including data types, basic programming, reading and writing data, installing packages, and basic statistics. The workshop also covers data manipulation and programming, plotting with ggplot2, and additional statistical tests, including summary statistics, parametric and non-parametric tests, and multiple regression.
Advanced Statistics in edgeR
Learn how to run pairwise, multi-group, and multi-factor statistics (e.g. one-way or two-way ANOVA, repeated measures), and batch effect corrections, in edgeR. Practice visualizing results in PCA plots and heatmaps. Applicable to RNA-seq, ChIP-seq, ATAC-seq, bisulfite-seq, and metagenomics.
Pre-requisites:
This workshop day assumes knowledge and skills that will be covered in R Essentials for Data Analysis workshop day (day 1). Registration for this pre-requisite days is strongly recommended unless the attendee is very confident in their abilities or has previously attended this workshop day. If an attendee opts out of pre-requisite workshop days, then they assume full responsibility for the level of skill required for the later workshop days.
Pathway Analysis
Review and discussion of databases, statistical methods, and tools available for pathway analysis, including Gene Ontology, KEGG, MSigDB/GSEA, and Ingenuity Pathway Analysis (IPA). Network analysis and visualizations discussed as well.
Pre-requisites:
This workshop day assumes knowledge and skills that will be covered in R Essentials for Data Analysis workshop day (day 1). Registration for this pre-requisite days is strongly recommended unless the attendee is very confident in their abilities or has previously attended this workshop day. If an attendee opts out of pre-requisite workshop days, then they assume full responsibility for the level of skill required for the later workshop days.
Single Cell RNA-seq
Single cell transcriptome quantification, quality control, normalization, and clustering. Statistical tests for differential expression and composition. Evaluating the robustness of results, and putative cell type identification. Integration of scRNA-seq with VDJ or feature profiling data, as well as trajectory analysis, will also be covered.
Pre-requisites:
This workshop day assumes knowledge and skills that will be covered in R Essentials for Data Analysis workshop day (day 1). Registration for this pre-requisite days is strongly recommended unless the attendee is very confident in their abilities or has previously attended this workshop day. If an attendee opts out of pre-requisite workshop days, then they assume full responsibility for the level of skill required for the later workshop days.
Machine Learning
Strategies for feature selection from -omics and clinical data sets, review of classification algorithms (e.g., Random Forest, Neural Net), machine learning model training, model evaluation (ROC/AUC, precision-recall, confusion matrix), and model interpretation for machine learning applications in -omics data sets.
Pre-requisites:
This workshop day assumes knowledge and skills that will be covered in R Essentials for Data Analysis workshop day (day 1). Registration for this pre-requisite days is strongly recommended unless the attendee is very confident in their abilities or has previously attended this workshop day. If an attendee opts out of pre-requisite workshop days, then they assume full responsibility for the level of skill required for the later workshop days.