Articles - Genomic data visualization

A heatmap (or heat map) is another way to visualize hierarchical clustering. It’s also called a false colored image, where data values are transformed to color scale. Heat maps allow us to... [Read more]

As described in previous chapters, a dendrogram is a tree-based representation of a data created using hierarchical clustering methods (Chapter @ref(agglomerative-clustering)). In this article,... [Read more]

After showing how to compute hierarchical clustering (Chapter @ref(agglomerative-clustering)), we describe, here, how to compare two dendrograms using the dendextend R package. The... [Read more]

The agglomerative clustering is the most common type of hierarchical clustering used to group objects in clusters based on their similarity. It’s also known as AGNES (Agglomerative Nesting). The... [Read more]

The k-medoids algorithm is a clustering approach related to k-means clustering (chapter @ref(kmeans-clustering)) for partitioning a data set into k groups or clusters. In k-medoids clustering,... [Read more]

K-means clustering (MacQueen 1967) is the most commonly used unsupervised machine learning algorithm for partitioning a given data set into a set of k groups (i.e. k clusters), where k represents... [Read more]

karyoploteR is an R/Bioconductor package to to plot virtually anything along the genome.

Installation:

Code R... [Read more]