HarvardX: PH525x Data Analysis for Genomics
Data Analysis for Genomics
The repository of the R markdown files (.Rmd) for the labs shown here is:
Resources
Introduction (week 1)
- Introduction
- Exploratory Data Analysis
- Installing Bioconductor and finding help
- R refresher
- Robust summaries
Microarray and NGS basics (week 2)
- Installing packages from Github
- Reading microarray data
- Downloading data from GEO using GEOquery
- EDA plots for microarray
- Basic Bioconductor infrastructure
- EDA plots for next generation sequencing
Statistical inference and linear modeling (week 3)
- Inference
- Expressing design formula in R
- Linear models
- Basic inference for microarray
- Rank tests
- Monte Carlo methods
Background, modeling and normalization (week 4)
Distance and prediction (week 5)
- Distance lecture
- Distance and clustering lab
- Dimension reduction and heatmaps
- Prediction lecture
- Cross-validation
Batch effect (week 6)
Advanced differential expression (week 7)
- Hierarchical modeling and using limma
- Mapping features to genes
- Gene set analysis lecture
- Gene set testing in R
- Multiple testing
Advanced workflows (week 8)
- Visualizing NGS data
- Counting NGS reads in features
- Methylation
- Reading 450K idat files with the minfi package
- Interactive visualization of DNA methylation data analysis
- ChIP-seq
- RNA-seq
- Genome variation
