Heat-map claim
This page has four parts, in the order you use them. Part 1 is what you need to know. Part 2 says what to do, in plain English. Part 3 shows the work done once on a case that is not yours. Part 4 is your own work and where to turn it in.
Open your materials, follow the steps, then turn in your work.
Read a microarray heat map and write a claim that separates disease risk from disease diagnosis.
Optional: listen or watch a unit review▸
Part 1 of 4 · Background and definitions▸
💡 Big idea: A encodes fold-change magnitude as color, so it can reveal an elevated-risk pattern, but because expression alone is not clinical confirmation, that pattern signals risk rather than a diagnosis.
- • A encodes fold-change magnitude as color intensity; clustering similar patterns reveals co-regulated gene groups.
- • A risk indicator shows an elevated probability of disease; a diagnosis requires clinical confirmation beyond expression data alone.
- • CER claims from data should be falsifiable: if the expression pattern reversed, what would that mean for your claim?
divides diseased expression by healthy expression, so a result above 1 means that gene is more active in the disease sample and a result below 1 means that gene is less active in the disease sample.
A encodes fold-change magnitude as color, so it can reveal an elevated-risk pattern, but because expression alone is not clinical confirmation, that pattern signals risk rather than a diagnosis.
Driving question: Looking at your own color-coded grid of fold-change values, which cluster of genes differs most between diseased and healthy, and does that pattern let you say a patient has the disease or only that they are at elevated risk?
What you already know: divides diseased expression by healthy expression, so a result above 1 means that gene is more active in the disease sample and a result below 1 means that gene is less active in the disease sample.
New idea: A encodes fold-change magnitude as color, so it can reveal an elevated-risk pattern, but because expression alone is not clinical confirmation, that pattern signals risk rather than a diagnosis.
Visual or model: No figure is attached to this lesson. The readings, the worked example and E1 to E3 carry the evidence.
- Observe or measure the relevant feature in heat-map claim.
- Organize the observation with a stable evidence ID.
- Apply this rule: Stored information can be copied, read, and converted into a functional product.
- Choose the option the evidence supports and state the limit of the conclusion.
Real biomedical example: Looking at your own color-coded grid of fold-change values, which cluster of genes differs most between diseased and healthy, and does that pattern let you say a patient has the disease or only that they are at elevated risk?
What the evidence supports: E1 to E3 support the daily take-home when the response meets the stated success criteria.
What it cannot prove: The package does not support claims beyond this lesson's or any real patient diagnosis.
- • : The process by which the information in a gene is used to build a working product, usually a , through and .
- • : A chip holding thousands of tiny spots that lets scientists measure the activity of many genes at once by detecting which spots light up.
- • : A grid where each square is coloured according to its value, so a table too large to read as numbers can be read as a pattern. On a each row is a gene, each column is a sample, and the colour shows how much of that gene the sample is making.
- • : How many times larger or smaller a measurement is than its reference. A of 3 means three times as much as the control. A fold change of 0.5 means half as much. A fold change of 1 means no change at all.
- • : Describing a gene or that the cell is making in larger amounts than usual, often in response to a signal or change in conditions.
- • : Describes a gene or whose activity or amount has been turned down, so the cell makes less of its product.
Use it now: Choose one decision option. Cite E1 and E3, then explain how the rule connects the evidence to your choice. This is thinking practice for the one turn-in named under Turn in, not a second submission.
Go further, optional: The source links below are optional enrichment. Every fact required for today's local evidence decision appears in this lesson package.
A gene-expression comparison describes relative signal patterns across the supplied conditions, and interpretation depends on normalization, replication, controls, measurement range, and the difference between association and causation.
Limit: A classroom expression table can support a bounded pattern claim but cannot diagnose disease, prove a regulatory mechanism, or establish clinical significance.
Stored information can be copied, read, and converted into a functional product.
Limit: Genes are regulated biological sequences, not conscious instructions, and one gene rarely determines a whole trait alone.
You can read clusters on a .
Limit: E3 defines the classroom product or success criterion. It is not independent scientific evidence and cannot justify a clinical or causal claim.
Today's decision · Simulated classroom evidence scenario
Your role: medical interventions team member
Decision: Your team must decide what the evidence from heat-map claim supports before submitting the claim-evidence-reasoning response named on today's page.
- • State that the patient has the disease, because the diseased cluster stands out so clearly on the grid.
- • Pause the claim until a clinical confirmation test is run, since expression can be elevated for many reasons.
- • Write the claim as elevated risk, since the color pattern shows expression differences and not clinical confirmation.
Response: State one choice, cite at least two evidence IDs, explain the rule that connects them, and add one limitation. Use it inside the one turn-in named under Turn in; it is not a separate submission.
Claim ceiling: Today's evidence supports a classroom claim about heat-map claim. It cannot prove causation, diagnose a real patient, or justify action outside this room.
Reason for review: Your team must decide what the evidence from heat-map claim supports before submitting the claim-evidence-reasoning response named on today's page.
Context: Data can shift the odds without settling the verdict, so a strong expression pattern is a reason to look harder, not a finished diagnosis.
- • T1: Shade your fold-change values from last class into a small , high values one color and low another.
- • T2: Identify the cluster of genes that differs most between diseased and healthy samples.
- • T3: Write a CER claim about what the pattern suggests, with two values as evidence.
- • T4: Add one sentence explaining why this pattern shows risk, not a confirmed diagnosis.
- • T5: Submit your and claim as your daily evidence.
- • E1: A gene-expression comparison describes relative signal patterns across the supplied conditions, and interpretation depends on normalization, replication, controls, measurement range, and the difference between association and causation.
- • E2: Stored information can be copied, read, and converted into a functional product.
- • E3: You can read clusters on a .
Measurements: Use only the measurements, units, graph, or counts supplied in today's task. No additional patient measurement is implied.
Uncertainty: This is a composite classroom scenario. Missing history, measurements, or confirmation tests remain unknown and limit the conclusion.
Sorted high to low: 3.1, 1.4, 0.8, 0.3. Gaps: 1.7, 0.6, 0.5. The biggest gap sits between 3.1 and 1.4, so the top value stands alone as the most cluster and the other three group together; shade darkest at the top of the sort.
Four practice fold-change values, not yours: 3.1, 1.4, 0.8, 0.3. Sort them, find the biggest gap between neighbors, and say where the cluster boundary falls.
A value near 1 belongs in the middle of the shading, not at either end; anything below 1 is no matter how the colors look.
Sort your own four values, mark the biggest gap, shade by rank, and use the two values on either side of the gap as the evidence in your claim.
Students often think a striking heat-map pattern is itself proof that the patient has the disease. The trap: A shows expression differences, and expression can be elevated for many reasons, so the pattern raises the probability of disease but does not confirm it. Calling risk a diagnosis is a trap because it skips the clinical confirmation a real patient still needs.
- 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. Find it in Clever with your Microsoft sign-in, right next to Schoology.
Tap the speaker to hear a term. Add two of these to your notebook glossary with a definition and an example in your own words.
Pick just 2 or 3 words from today and make them yours: write what each one means in your own words, name the context clue or evidence that helped, then give one example from what you actually did in Heat-map claim. Try your own words first; the glossary is there if you get stuck. This is voluntary and counts as extra credit, so keep it short.
Saved on this device. Show Mr. Mendoza or add these to your notebook glossary to claim the extra credit.
Part 2 of 4 · Directions in plain English▸
2.1 Open your materials
Use the materials named in the first step below. Open lesson resources.
2.2 Start the work
Shade your fold-change values from last class into a small heat map, high values one color and low another.
Show all 5 required steps
- Shade your fold-change values from last class into a small heat map, high values one color and low another.
- Identify the cluster of genes that differs most between diseased and healthy samples.
- Write a CER claim about what the pattern suggests, with two values as evidence.
- Add one sentence explaining why this pattern shows risk, not a confirmed diagnosis.
- Submit your heat map and claim as your daily evidence.
Lost your place? Pull up your fold-change values from the expression lab and restart at step 1: shade high values one color and low values another, then find the cluster that differs most before you write your claim.
- 0-8Hook heat maps; review risk vs. diagnosis distinction
- 8-25Shade fold-change values from last class into grid (high = one color, low = another)
- 25-45Identify the gene cluster with the greatest diseased-vs.-healthy difference
- 45-60Write CER claim using two specific fold-change values as evidence
- 60-72Add risk-vs.-diagnosis sentence; peer check for accuracy
- 72-80Submit and claim in Schoology; preview Friday report
- • Hook: Show two heat maps: one from a healthy subject, one from a diagnosed patient, and ask students to point to the biggest difference.
- • Why it matters: Clinicians use expression clusters to decide which patients need follow-up biopsies or monitoring.
- • Today's work: You shade your own data into a and write the claim a clinician would write, carefully distinguishing risk from diagnosis.
- • Exit goal: and CER claim submitted before the bell.
PLTW connection and today's work
Open Activity 3.1.4 DNA Microarray in myPLTW and shade your fold-change values into a heat map to identify the gene cluster with the greatest difference.
Today's stopping point: Fold-change table should be done; heat map and CER claim due today.
PLTW activity titles identify the course connection. If your account will not open, use the posted materials for today and tell Mr. Mendoza. Do not mark an online activity complete unless you completed it.
Use the turn-in directions in Part 4 of this page. Do not create a second submission unless your teacher asks for one.
Show another explanation or a smaller first step
Need help? Choose a starting point
Part 3 of 4 · Worked example▸
This is a parallel case, not your own. Read it for the order of the work, then do your own in Part 4.
Note: This is a parallel model on a different practice grid (Genes W, X, Y, Z), not the heat-map task you are doing today. Use it to see the CER format and depth, then build your own claim from your own values.
I sorted the four practice fold-change values (Gene W 3.5, Gene X 1.2, Gene Y 0.9, Gene Z 0.2) and shaded them darkest to lightest.
Claim: This practice sample shows an expression pattern consistent with elevated risk of the disease, driven by one strongly upregulated gene, but it does not confirm the disease.
Evidence: Gene W at 3.5 is far above 1 and stands alone after the biggest gap in the sort; Gene Z at 0.2 is strongly downregulated. Genes X and Y sit near 1 and carry no signal.
Reasoning: A gene far above 1 beside one far below 1 is the kind of pattern that raises the probability of disease, but one practice sample cannot tell a real pattern from noise; that takes replicate measurements of the same genes in more samples. It stays risk, not diagnosis, because expression can be raised for reasons other than the disease and no clinical test has confirmed it.
Limitation: Four genes in one sample is a small window; the claim needs replicate measurements, many more genes, and comparison samples with a confirmed diagnosis.
| Gene | Fold change | Heat-map shade |
|---|---|---|
| Gene W | 3.5 | darkest (up) |
| Gene X | 1.2 | pale, near 1 |
| Gene Y | 0.9 | pale, near 1 |
| Gene Z | 0.2 | lightest (down) |
This model shows the level of evidence and organization needed to complete: Parallel worked CER on a different four-gene practice grid (Genes W to Z, values that are not yours): a shaded heat map and a claim with two fold-change values as evidence that separates elevated risk from diagnosis. Models the format only. Your own heat-map claim uses your own grid.
- Write one defensible claim.
- Choose specific evidence that supports the claim.
- Explain the scientific rule that connects the evidence to the claim.
Keep the structure. Replace the question, facts, measurements, and evidence. Then recheck units, vocabulary, and whether the conclusion goes beyond the evidence.
Also due today: Submit your heat map and claim in Schoology.
A library keeps a master plan protected while working copies guide production at different stations.
- Why protect the master copy?
- What information moves?
- Where can an error change the final product?
Stored information can be copied, read, and converted into a functional product.
Genes are regulated biological sequences, not conscious instructions, and one gene rarely determines a whole trait alone.
- • Master plan maps to .
- • Working copy maps to RNA.
- • Production output maps to or a regulated cell function.
Part 4 of 4 · Your work▸
Check your work before submitting
- You'll be able to read clusters on a heat map.
- You'll be able to distinguish risk from diagnosis in your claim.
4.1 Turn in your work
DueCheck the Schoology assignment for this day- Hand in
- Shaded heat map of four genes and a CER claim (claim, two fold-change values as evidence, reasoning) that distinguishes risk from diagnosis.
How to submit and name your file
Submit as one PDF in Schoology.
In Schoology, open your course and the assignment for this lesson. Attach your file, select Submit, and check that it appears in the submission.
PDF upload helpYou get two school days for every day you were absent, so this deadline moves with you.
Today's lesson is in Schoology
Each school day has one lesson page in Schoology that holds everything for the day: the goal, the story so far, every table and data value, the numbered steps, and what to turn in. Open it first and work from it. The other rows for this day, if any, are the score line for a paper quiz or test and the John Carroll debate item; they do not add work. Check Schoology for each deadline.
- Today's Lesson · Wed 10/28 · Wk10 · Read the gel for Sue and four friends, then a guide to prenatal tests(today's lesson page: the goal, the data, the steps, and what to turn in are all on it)
Link will not open? Open Schoology, choose your course and section, and find the title shown above.
- 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.
- SubmittedGo to Schoology to turn this in. Submit one PDF. Schoology attaches your name to your upload; on the page itself, write your period and code. Name the file: FirstName LastName - Assignment Title - YYYY-MM-DD.pdf. If you cannot get in, see Mr. Mendoza. Do not skip the work.
How this lesson connects
Keep using what you learned last class: Fold change divides diseased expression by healthy expression, so a result above 1 means that gene is more active in the disease sample and a result below 1 means that gene is less active in the disease sample. Today: A heat map encodes fold-change magnitude as color, so it can reveal an elevated-risk pattern, but because expression alone is not clinical confirmation, that pattern signals risk rather than a diagnosis.
Practice: try a question, then check your answer▸
Claim ceiling for this check: Today's evidence supports a classroom claim about heat-map claim. It cannot prove causation, diagnose a real patient, or justify action outside this room.
Your heat map shows a bright cluster of upregulated genes in the diseased sample. A classmate writes: 'This proves the patient has the disease.' Fix the claim so it is scientifically honest.
Write an answer and pick a confidence to unlock the key.
Missed class or ready for more?▸
Optional practice for this unit's lab skills. Nothing in it is due today.
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.
Follow from gene to , and see why the lip and need it.
Goes with: From gene to protein: IRF6 has a job
Five genes, five ways to interrupt a face: , , CDH3, MSX1, .
Goes with: The cleft gene set: more than one way to interrupt a face
Today is individual work you can do from home: complete the same target above, then submit your CER.
Go to Schoology to turn this in. Submit one PDF. Schoology attaches your name to your upload; on the page itself, write your period and code. Name the file: FirstName LastName - Assignment Title - YYYY-MM-DD.pdf. If you cannot get in, see Mr. Mendoza. Do not skip the work.
Class still runs. Complete today's work as this page describes (it is self-guided). Need the concept taught without a teacher? Use this authoritative explainer:
Genetic Science Learning Center: Genes and gene expressionThe optional extra-credit track is open. Complete reserved-unit work from home, including virtual labs, for extra credit. Each item shows its correct submission route.
Open the extra-credit trackSources: slides, readings, and resources▸
The deck carries the prior idea forward, lets you inspect an analogy, maps the rule to biology, and ends with the same evidence decision and exit ticket used on this page.
Classroom documents for this lesson are posted in Schoology. Open Clever, then Schoology, and find each one by the name shown on its card.
Use this as the classroom resource for and analysis.
Use this if you were absent, got stuck, or need another pass before you submit the lesson artifact.
Use this if you were absent, got stuck, or need another pass before you submit the lesson artifact.
Sign in to Clever with your district Microsoft account to open Schoology or myPLTW. Follow today's posted steps. If myPLTW will not open, use the posted alternative and tell Mr. Mendoza. Turn in your completed work through the Schoology assignment.
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