Visualising differences in protein binding
Both PCA plot and dendrogram indicate that the samples from primary tumors and treatment-resistant tumors from one cluster each. This is encouraging but tells you very little about what these differences look like. In this exercise, you will create a heatmap that compares peak intensity across samples. This can help to highlight patterns in protein binding that distinguish between groups of samples.
The set of peaks, consolidated across samples, is available as peaks. To create a heatmap of peaks from this, you'll have to know
how many peaks there are in the dataset. Details of the merged peak set are available in the merged entry of peaks.
This exercise is part of the course
ChIP-seq with Bioconductor in R
Exercise instructions
- Print the
peaksobject. - Obtain the coordinates of the merged peaks.
- Extract the number of peaks present in the data.
- Create a heatmap using the
dba.plotHeatmapfunction.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Print the `peaks` object
print(___)
# Obtain the coordinates of the merged peaks
merged_peaks <- peaks$___
# Extract the number of peaks present in the data
peak_count <- nrow(___)
# Create a heatmap using the `dba.plotHeatmap()` function
___(peaks, maxSites = ___, correlations = FALSE)