Expression data lab
Use a gene expression table to calculate fold change and flag upregulated and downregulated genes.
Fold-change table for four genes with upregulated/downregulated labels and one sentence on the biological meaning of an upregulated gene.
- 1Do thisUse a gene expression table to calculate fold change and flag upregulated and downregulated genes.
- 2Use this resource
- 3Submit thisData table: Fold-change table for four genes with upregulated/downregulated labels and one sentence on the biological meaning of an upregulated gene.
- 4Submit it here
- 1CMSD website. Go to clevelandmetroschools.org and click the Clever button.
- 2Clever. Clever opens. Sign in if it asks.
- 3Microsoft (district) login. Use your district Microsoft account (the one for school).
- 4Schoology. Open Schoology, then your class, then Assignments, and find the file named below.
The file to submit is named: Genetics of Disease (Medical Interventions) › Differential expression, fold change, correlation, disease risk vs. diagnosis. › Data tableOpen Schoology
- CER:
- Claim, Evidence, Reasoning — make a claim, back it with evidence, explain your reasoning.
- SOP:
- Standard Operating Procedure — the exact steps to follow (especially in a lab).
- Tracker:
- Your PLTW progress log where you record completed evidence.
- myPLTW:
- The PLTW course site where you do the online activities — you open it through Schoology.
Minute-by-minute · 80-minute block
💡 Big idea: How do numbers in a spreadsheet reveal which genes a disease turns on or off?
- 0-8Hook heat map and fold-change formula introduction; confirm dataset access
- 8-25Open dataset; locate diseased and healthy columns; calculate fold change for genes 1-2
- 25-45Calculate fold change for genes 3-4; label all four as up or downregulated
- 45-60Write one sentence on what an upregulated gene might mean for the disease
- 60-72Partner check: verify each other's calculations for arithmetic errors
- 72-80Save fold-change table to course shell; preview Thursday heat-map work
- • Hook: Show a heat map of cancer vs. normal tissue and ask: which genes are the disease turning up, and which is it turning off?
- • Why it matters: Gene expression analysis is how researchers identify cancer biomarkers and drug targets.
- • Today's work: You apply the fold-change formula to real expression data and interpret what the numbers mean.
- • Exit goal: Fold-change table with upregulated/downregulated labels and one interpretation sentence saved before the bell.
- 1Open the expression dataset in the shell and find the diseased and healthy sample columns.
- 2For four genes, calculate fold change by dividing diseased expression by healthy expression.
- 3Label each gene upregulated or downregulated based on whether fold change is above or below one.
- 4Write one sentence on what an upregulated gene might mean for the disease.
- 5Save your fold-change table as your lab evidence.
- • You'll be able to calculate fold change from expression data.
- • You'll be able to flag genes as upregulated or downregulated.
- • Fold change = diseased expression / healthy expression; greater than 1 is upregulated, less than 1 is downregulated.
- • Microarray data is generated by measuring fluorescence intensity at each probe spot; the numbers in the dataset represent those intensities.
- • An upregulated gene in diseased tissue may be driving the disease (oncogene) or responding to protect cells (repair gene).
Your PLTW work today
Differential expression, fold change, correlation, disease risk vs. diagnosis. · Expression data lab
Day 1 of this lesson. Open this exact section in myPLTW (reached through Schoology), then do the work below.
Do this: Open Activity 3.1.5 Unlocking the Secrets in Our Genes in myPLTW and use the gene expression dataset to calculate fold change for four genes.
Mark the expression data activity complete after your fold-change table is saved.
No school Monday/Tuesday; this data lab is the opening hands-on benchmark for this unit.
Fold-change table for four genes with upregulated/downregulated labels saved in the course shell.
All PLTW activities are completed inside the PLTW course environment — this page only gives direction. Submit producibles on Schoology.
Today's PLTW tracker
Check things off as you work, then submit. This tells Mr. Mendoza how you're doing so he can help the class. It does not replace turning in your producible on Schoology.
Use the code Mr. Mendoza gave you, not your name. Saved on this device.
Differential expression, fold change, correlation, disease risk vs. diagnosis. · Expression data lab
Open Activity 3.1.5 Unlocking the Secrets in Our Genes in myPLTW and use the gene expression dataset to calculate fold change for four genes.
No school Monday/Tuesday; this data lab is the opening hands-on benchmark for this unit.
This is how Mr. Mendoza sees the class keeping pace with PLTW. Be honest, it only helps if it is accurate.
🎯 Use a gene expression table to calculate fold change and flag upregulated and downregulated genes.
- Open the expression dataset in the shell and find the diseased and healthy sample columns.
- For four genes, calculate fold change by dividing diseased expression by healthy expression.
- Label each gene upregulated or downregulated based on whether fold change is above or below one.
- Write one sentence on what an upregulated gene might mean for the disease.
- Save your fold-change table as your lab evidence.
Data table: Fold-change table for four genes with upregulated/downregulated labels and one sentence on the biological meaning of an upregulated gene.
Submit on SchoologyUpload by 11:29 PM for full credit.
| Task | Who |
|---|---|
| Open the expression dataset in the shell and find the diseased and healthy sample columns. | _______ |
| For four genes, calculate fold change by dividing diseased expression by healthy expression. | _______ |
| Label each gene upregulated or downregulated based on whether fold change is above or below one. | _______ |
| Write one sentence on what an upregulated gene might mean for the disease. | _______ |
| Save your fold-change table as your lab evidence. | _______ |
Working solo? Put your own name in "Who" for every row.
- You'll be able to calculate fold change from expression data.
- You'll be able to flag genes as upregulated or downregulated.
Teacher-posted resources
Classroom documents for this lesson. Ones marked “Open the file” open right here; the rest are posted in Schoology. Use the label on each card to choose the right move.
Use this as the classroom resource for Gene expression and microarray analysis.
Placement rationale
Matched Gene expression and microarray analysis by path:Medical-Interventions/Unit-2_How-to-Screen-Your-Genes/00_Unit-Overview; keywords:gene expression, microarray. Score 138. Visibility: student-schoology (student-facing resource; link through Schoology rather than local path).
Use this if you were absent, got stuck, or need another pass before you submit the lesson artifact.
Placement rationale
Matched Gene expression and microarray analysis by path:Medical-Interventions/Unit-2_How-to-Screen-Your-Genes/00_Unit-Overview; keywords:microarray. Score 126. Visibility: student-schoology (student-facing resource; link through Schoology rather than local path).
Use this if you were absent, got stuck, or need another pass before you submit the lesson artifact.
Placement rationale
Matched Gene expression and microarray analysis by path:Medical-Interventions/Unit-2_How-to-Screen-Your-Genes/2.1_Genetic-Testing-and-Screening. Score 126. Visibility: student-schoology (student-facing resource; link through Schoology rather than local path).
How to get there: open the CMSD website, click Clever, sign in with your Microsoft (district) account, then open Schoology from Clever.
Lab & supplies
- • No wet lab materials today; all work is computational.
- • Dataset is anonymized class-aggregate; do not enter or share personal identifying information.
- • Save your work frequently; do not rely on browser auto-save for the dataset.
WebXam practice
Cumulative WebXam review
A quick mixed-review pulling questions from earlier units plus today, so the WebXam material stays fresh.
Where this leads — careers
What today's skills lead to. These are real health-science careers this course builds toward. Tap one to see, on the US Department of Labor's O*NET site, what the job actually involves, what it pays, and how fast it is growing.
What to do if you were absent
From home, open the provided expression spreadsheet and complete the same analysis: calculate fold change for four genes, label each up or downregulated, and shade a small heat map by value.
Gene expression dataset (PLTW course shell)Then submit your Data table on Schoology.
Class still runs. Complete the online activity above (it's self-guided). Need the concept taught without a teacher? Use this authoritative explainer:
Genetic Science Learning Center: Genes and gene expressionOptional extra credit (async)
You've passed Unit 2, so the optional extra-credit track is open. Complete reserved-unit work from home (virtual labs included) for extra credit, all submitted on Schoology.
Open the extra-credit track- CompleteEvery required part of the artifact is present, nothing left blank.
- AccurateThe science and the data are correct and match the evidence.
- Scientific reasoningYou explain your claim with evidence and reasoning (CER), not just an answer.
- Professional communicationClear, organized, labeled, and written the way a clinician or scientist would.
- SubmittedTurned in the right way (Schoology for routine work) and confirmed.
Drop your Wed, Mar 24, 2027 · Expression data lab here. Use a clear file name (your initials + project). Routine work still goes to Schoology (via the CMSD portal).
Upload a project