1 Setup

First things first: install pcaExplorer and load it into your R session. You should receive a message notification if this is completed without errors.

BiocManager::install("pcaExplorer")
library("pcaExplorer")

This document describes a use case for pcaExplorer, based on the dataset in the airway package. If this package is not available on your machine, please install it by executing:

BiocManager::install("airway")

This dataset consists of the gene-level expression measurements (as raw read counts) for an experiment where four different human airway smooth muscle cell lines are either treated with dexamethasone or left untreated.

2 Start exploring - the beauty of interactivity

To start the exploration, you just need the following lines:

library("pcaExplorer")
pcaExplorer()

The easiest way to explore the airway dataset is by clicking on the dedicated button in the Data Upload panel. This action will:

  • load the airway package
  • load the count matrix and the experimental metadata
  • compose the dds object, normalize the expression values (using the robust method proposed by Anders and Huber in the original DESeq manuscript), and compute the variance stabilizing transformed expression values (stored in the dst object)
  • retrieve the gene annotation information via the org.Hs.eg.db, adding gene symbols to the ENSEMBL ids - this step is optional, but recommended for more human-readable identifiers to be used.

If you want to load your expression data, please refer to the User Guide, which contains detailed information on the formats your data have to respect.

Once the preprocessing of the input is done, you should get a notification in the lower right corner that youโ€™re all set. The whole preprocessing should take around 5-6 seconds (tested on a MacBook Pro, with i7 and 16 Gb RAM). You can check how each component looks like by clicking on its respective button, once they appeared in the lower half of the panel.