Made by David Requena (drequena@rockefeller.edu) and James Saltsman (jsaltsman@rockefeller.edu).
This code includes some basic steps:
- SET UP:
- Install and/or call the required libraries
- Input sample metadata
- Create the DESeq2 object
- Exploring the data:
- Transformations of the Data
- PCA plot
- tSNE plot
- HeatMap
- Data Analysis:
- Model matrix
- Comparison
- Annotation and output tables
- Plots:
- Histogram of p-values
- Dispersion Estimates
- MA Plot
- Volcano Plot
- HeatMap with genes
- BoxPlot and ScatterPlot
To run this script, two tables are required:
- A table with the samples' data, containing features of interest (e.g. cases/controls, gender, etc...)
- A table with the gene counts by sample
And two optional tables:
- A table with genes to be filtered out (e.g. ribosomal genes)
- A table with genes of interest, to prepare individual plots by gene