Large biological datasets are often too big to understand by reading numbers in a table. In DREAM-High, we will eventually use heatmaps to look for patterns in breast cancer gene expression data from patients in The Cancer Genome Atlas. A heatmap can help us ask questions such as: - Which samples look similar to each other? - Which genes behave similarly across patients? - Can visual patterns help us discover tumor subtypes? Today we will learn the same basic idea using a small practice dataset that comes with R.

Cancer datasets often contain thousands of measurements for each sample. For example, a single cell line or patient tumor may have expression measurements for thousands of genes.

Now we will use real gene expression data from TCGA breast cancer samples. Gene expression data which tells us how many messenger RNAs (mRNAs) per gene are present in a patient sample. The amount of a gene's mRNA corresponds (roughly) to the amount of protein in the sample.

Math problems of the day for 8/3/26.