Tag Archives: Hierarchical Clustering

With the increasing availability of multi-dimensional biological datasets for the same samples (i.e., gene expression, microRNAs, copy numbers, mutations, methylations), it has now become possible to systematically understand the regulatory mechanisms operating in a cancer cell. For this task, it ...

Advice from Charlotte Soneson, Qlucore Introduction Graphical representations of high-dimensional data sets are at the backbone of straightforward exploratory analysis and hypothesis generation. Within the life sciences, two of the most commonly used methods for this purpose are heatmaps combined ...

Sample- and gene- based hierarchical cluster analyses have been widely adopted as tools for exploring gene expression data in high-throughput experiments. Gene expression values (read counts) generated by RNA sequencing technology (RNA-seq) are discrete variables with special statistical properties, such ...