In the previous heatmap activity, we used the small built-in mtcars dataset. That was useful because the dataset was small enough to see clearly. 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. This is more realistic, but also more challenging: there are many genes there are many patient samples the data are noisy not every plot gives a perfect, simple answer That is normal in real computational biology. Our goal is to use heatmaps to ask: Do breast tumors with similar gene expression patterns also share clinical features, such as estrogen receptor status?

In previous DREAM-High activities, we studied cancer patient data from TCGA. Here we switch to a different kind of cancer model: human cancer cell lines. Cancer cell lines are cells that can grow in the laboratory. Researchers use them to study cancer biology and to test hypotheses about cancer behavior. In this activity, we will compare two breast cancer cell lines: T-47D MDA-MB-231 We will ask: Do differences in cell movement correspond to differences in gene expression? This is a core idea in systems biology: we connect a measurable behavior, or phenotype, to molecular data.

In the previous heatmap activity, we used the small built-in mtcars dataset. That was useful because the dataset was small enough to see clearly. 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. This is more realistic, but also more challenging: there are many genes there are many patient samples the data are noisy not every plot gives a perfect, simple answer That is normal in real computational biology. Our goal is to use heatmaps to ask: Do breast tumors with similar gene expression patterns also share clinical features, such as estrogen receptor status?

Charts created analyzed using data from a sample of breast cancer patients