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 TCGA
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
VIDEO ABSTRACT
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