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?

Scatterplot with tooltips

Fixed Effects

generated on July 24th at 14:40

Short summary of mbadtools package and tools

Assignment 8

Structural Equation Model using same dataset used for the Rasch analysis. The results were not as I expected - none of the predictor variables predicted income.