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Analyses of TCGA Genomic and Epigenomic Data Workshop, 10-11th of July 2018, Poznan, POLAND

Conference and Teaching Center, C room, ul. Przybyszewskiego 37a, 60-356 Poznan, Poland

Day 1

10.07.2018; 10am - 5pm; lunch break 1-2pm

1. Introduction to R: slides | code | script1 | data

2. Analyses: slides | code | expression data | GO annotation
o Introduction
o Differential expression analysis
o Enrichment analysis
o Clustering, dendrograms and heatmaps
o Principal component analysis
o Survival analysis

3. NGS data: slides | code
o Introduction
o TCGAbiolinks: slides | code

4. TCGAbiolinks functionalities in R: code | data
o Different cancer datatypes
o Data retrieval code
o Functionality overview
o Case studies (focus on Case Study 1: BRCA GE and Survival)

Day 2

11.07.2018; 10am - 5pm; lunch break 1-2pm

1. Analyses with graphical interface: TCGAbiolinksGUI: slides | data
o Integrative analysis: epigenomic and transcriptomics

2. Moonlight functionalities in R: slides | code
o TCGA Data retrieval
o GEO Data retrieval
o Differential phenotype analysis (DPA)
o Functional enrichment analysis (FEA)
o Gene regulatory networks (GRN)
o Upstream regulatory analysis (URA)
o Pattern Recognition analysis (PRA)

3. TCGA PanCancer Stemness: Training a stemness signature and applying it to score TCGA samples using one-class model
PanCanStem Workflow | code
o Training One-Class model using ES class from PCBC dataset
o TCGA PanCan33 Data retrieval
o TCGA BRCA 10 samples Data retrieval
o Deriving stemness signature for TCGA samples

Resources and literature:
GDC website for the TCGA PanCancer Stemness project
Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation Cell 173:338, 2018
One-Class Detection of Cell States in Tumor Subtypes Pac Symp Biocomput. 21:405, 2016
Pathway-Based Genomics Prediction using Generalized Elastic Net PLoS Comput Biol. 12, 2016


o R libraries: Day 1 | Day 2 | TCGAbiolinksGUI
o Package vignette and vignette source
o Package workflow


R Reference Card
Swirl - Learn R, in R
Data Mining Algorithms In R
One Page R: A Survival Guide to Data Science with R
Introduction to Machine Learning
Google's R Style Guide
Advanced R programming
A Guide to Speeding Up R Code for Busy People
The R inferno
Resources to help you learn and use R
Tools for Reproducible Research