I am an intern tasked with a project.

I have a dataframe of approximately 200 genes in 7 tissues, showing the correlation of their expression across various timepoints. My next step is to find which genes have similar expression patterns in all of the tissues. AI tells me that hierarchal clustering would be the best method, but I couldn't find/understand anything on Google. Im not sure if I should flatten my data (e.g. Tissue_timepoint, Brain_P1) and do normal k means clustering, as I have read that it results in some loss in information. Any advice or links to resources would be appreciated.