Expression data lab
Wed, Nov 18, 2026 · Week 13 · Genetics of Disease (Medical Interventions)
Today's goal: Use a gene expression table to calculate fold change and flag upregulated and downregulated genes.
What a finished product looks like
This is a model of the work you should turn in today. Use it to check your own: match the structure and the level of detail, do not copy it. Your data and wording should be your own.
This is a parallel example on different data, untreated versus drug-treated cells, so you can see the method and then run it on today's own healthy-versus-diseased numbers.
I divided each gene's treated value by its untreated value to get fold change, then labeled each gene.
Rule I used: fold change above 1 is upregulated (more active after treatment); below 1 is downregulated (less active).
What an upregulated gene might mean: A gene turned up after treatment could be a stress-response gene the drug switched on, or a gene the drug was meant to boost, so the number flags a gene worth investigating, not an automatic cause.
| Gene | Untreated | Treated | Fold change | Label |
|---|---|---|---|---|
| Gene A | 40 | 120 | 3.0 | upregulated |
| Gene B | 250 | 50 | 0.2 | downregulated |
| Gene C | 30 | 150 | 5.0 | upregulated |
| Gene D | 200 | 80 | 0.4 | downregulated |
Also due today: Save your fold-change table to the course shell.
WebXam problem for today's skill
One exam-style question that uses exactly what you practiced today. Try it before you reveal the answer, then read why each choice is right or wrong.
Tap an answer to see the full explanation. Nothing is recorded or graded.