E-value and query coverage
Safety gate · before any work
- Wear the required PPE, keep the bench clear, handle equipment only as directed, and know where the eyewash, sink, and spill kit are before you start.
- Human samples and data stay private: label with a code, never a name, and dispose of materials in the correct waste container, then wash your hands.
Do now
Interpret E-value and query coverage to judge how trustworthy a BLAST match really is.
- Hand in
- Two-hit comparison table (E-value, query coverage, percent identity) and revised identification statement citing all three metrics.
- Where
- Turn this in at the drop folder with your district Microsoft sign-in, or hand it to Mr. Mendoza in class. Both count as submitted. Doing the activity in myPLTW does not.
You get two school days for every day you were absent, so this deadline moves with you.
Two hits both show 99 , but one matched your whole sequence and the other matched only a tiny piece. Which one is the real ID of your , and how do the numbers prove it?
Interpret E-value and to judge how trustworthy a match really is.
- • You will be able to explain what E-value and measure.
- • You will be able to rank two matches by reliability.
- • You will be able to support an identification with match-quality numbers.
- In your own words, what does measure? (Notes closed.)
- If two matches have the same , name one thing that could still make one of them more trustworthy than the other.
- 1Reopen your results and find the E-value and for your top hit.
- 2Write what each means: E-value as how likely the match is by chance, coverage as how much aligned.
- 3Compare two hits and decide which is stronger using both numbers.
- 4Note the rule: a smaller E-value and higher coverage mean a more reliable match.
- 5Flag any hit that looks high in identity but low in coverage and explain the risk.
- 6Revise your identification statement to cite E-value and coverage.
What did this day actually feel like?
E-value and query coverage
The part that separates a real match from a coincidence. A low E-value means the match is unlikely to be chance, and query coverage tells you how much of your sequence actually lined up.
You can get a confident-looking top hit that covers a tiny fraction of your sequence and means nothing. I would absolutely have been fooled by that yesterday.
Turned in: data table → Data Tables folder
Fiction. There is no such student. The lessons, labs and dates are the real planned course; the student, the classmates and the conversations are invented.
The same day, drawn.
The part that separates a real match from a coincidence. A low E-value means the match is unlikely to be chance, and query coverage tells you how much of your sequence actually lined up.
Fiction. There is no such student. The lessons, labs and dates are the real planned course; the student, the classmates and the conversations are invented.
🛠 Get unstuck · pick your level
Lab day: Tier 1 is the whole class at the bench. No extension today.
🔑 Today's words · 5
Tap a word in the lesson for a plain meaning and one example. Recycled into next week's Do-Now.
Do the work · 80-minute blockfirst 5 min = hook▸
💡 Big idea: A short region can match by chance, so a trustworthy identification needs high , a low E-value, and high together, because any one number alone can be fooled.
- 0-10 minReopen Wednesday's results; find and label E-value, , and for the top hit
- 10-25 minWrite plain definitions of E-value and in your notebook
- 25-40 minCompare two hits from the results: rank them using all three numbers and explain which is stronger and why
- 40-55 minFlag any hit with high identity but low coverage; write one sentence explaining the reliability risk
- 55-70 minRevise your identification statement to cite E-value, , and
- 70-80 minShare revised statement with a partner; check that all three numbers are cited correctly
- • alone can fool you: a 99% match over 10 bases is meaningless; a 95% match over the full sequence is strong.
- • E-value and are the two numbers scientists use to decide if a match is real or just statistical noise.
- • Today you apply these criteria to your Wednesday results and revise your identification with quantitative support.
- • Exit goal: a revised identification statement citing all three match-quality numbers.
- • E-value is the expected number of matches that random chance would produce; a smaller E-value means the match is less likely to be coincidence.
- • tells you what fraction of your sequence was aligned; low coverage means only a short region matched, which is unreliable.
- • A trustworthy identification requires high , low E-value, AND high together.
DNA identification, sequencing, BLAST, controls, query coverage, and E-value. · E-value and
Day 3 of this lesson. Open this exact section in myPLTW (find it in Clever, Microsoft sign-in), then do the work below.
Do this: Reopen your results in myPLTW Activity 1.1.3 and focus on interpreting E-value and for your top hit.
Complete the two-hit comparison and write a revised identification statement citing E-value, , and .
screenshot should be done (Wednesday); revised identification statement due today.
Revised identification sentence in notebook citing all three metrics.
The official PLTW activity stays inside myPLTW. If myPLTW will not open, use F1 and E1-E3 on this page to complete today's local evidence decision, then make up the official activity when access returns. Turn this in at the drop folder with your district Microsoft sign-in, or hand it to Mr. Mendoza in class. Both count as submitted. Doing the activity in myPLTW does not.
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 through the submission route shown below.
Use the code Mr. Mendoza gave you, not your name. Saved on this device.
DNA identification, sequencing, BLAST, controls, query coverage, and E-value. · E-value and query coverage
Reopen your results in myPLTW Activity 1.1.3 and focus on interpreting E-value and for your top hit.
screenshot should be done (Wednesday); revised identification statement due today.
This is how Mr. Mendoza sees the class keeping pace with PLTW. Be honest, it only helps if it is accurate.
🎯 Interpret E-value and to judge how trustworthy a match really is.
- Reopen your results and find the E-value and for your top hit.
- Write what each means: E-value as how likely the match is by chance, coverage as how much aligned.
- Compare two hits and decide which is stronger using both numbers.
- Note the rule: a smaller E-value and higher coverage mean a more reliable match.
- Flag any hit that looks high in identity but low in coverage and explain the risk.
- Revise your identification statement to cite E-value and coverage.
Data table: Two-hit comparison table (E-value, , ) and revised identification statement citing all three metrics.
Turn this in at the drop folder with your district Microsoft sign-in, or hand it to Mr. Mendoza in class. Both count as submitted. Doing the activity in myPLTW does not. Use the checklist just below and upload by 11:29 PM for full credit. Absent with an excused absence? You get two school days for every day you were absent, so this deadline moves with you.
| Task | Who |
|---|---|
| Reopen your results and find the E-value and for your top hit. | _______ |
| Write what each means: E-value as how likely the match is by chance, coverage as how much aligned. | _______ |
| Compare two hits and decide which is stronger using both numbers. | _______ |
| Note the rule: a smaller E-value and higher coverage mean a more reliable match. | _______ |
| Flag any hit that looks high in identity but low in coverage and explain the risk. | _______ |
| Revise your identification statement to cite E-value and coverage. | _______ |
Working solo? Put your own name in "Who" for every row.
- You will be able to explain what E-value and measure.
- You will be able to rank two matches by reliability.
- You will be able to support an identification with match-quality numbers.
- 1Do thisInterpret E-value and query coverage to judge how trustworthy a BLAST match really is.
- 2Use this resource
- 3Submit thisData table: Two-hit comparison table (E-value, query coverage, percent identity) and revised identification statement citing all three metrics.
- 4Submit it here
- 1Open the drop folder.
- 2Sign in with your district Microsoft account, not a personal one.
- 3Upload the file, named Lastname_Firstname__Assignment Title.
- 4Your own upload panel says Uploaded with a green check: that is your receipt.
Turn this in at the drop folder with your district Microsoft sign-in, or hand it to Mr. Mendoza in class. Both count as submitted. Doing the activity in myPLTW does not. Genetics of Disease (Medical Interventions) › DNA identification, sequencing, BLAST, controls, query coverage, and E-value. › Data tableOpen the drop folder
Learn it · deck, reading, and vocabulary▸
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.
Generated from this lesson's canonical data with a red-team citation check.
aligns your unknown read against millions of known sequences and ranks the matches, so a strong top hit names the organism, but only a passing control run proves the answer can be believed.
A short region can match by chance, so a trustworthy identification needs high , a low E-value, and high together, because any one number alone can be fooled.
An airport checkpoint uses several imperfect checks before deciding what action to take.
- What can each check detect?
- What might create a false alarm?
- Why is one result not always enough?
A decision is stronger when the test fits the question and its limits are known.
Medical decisions also depend on biology, patient context, ethics, and professional judgment.
- • Checkpoint evidence maps to E1-E3.
- • False alarms map to test limitations.
- • The response maps to the justified next intervention or test.
Driving question: Two hits both show 99 , but one matched your whole sequence and the other matched only a tiny piece. Which one is the real ID of your , and how do the numbers prove it?
What you already know: aligns your unknown read against millions of known sequences and ranks the matches, so a strong top hit names the organism, but only a passing control run proves the answer can be believed.
New idea: A short region can match by chance, so a trustworthy identification needs high , a low E-value, and high together, because any one number alone can be fooled.
Visual or model: F1. F1. A lesson illustration or teaching diagram for E-value and query coverage. Use it with E1-E3; it is a model or context image, not experimental or patient data. What to notice: Trace the labeled testing, treatment, or biological process and identify where evidence limits the decision.
- Observe or measure the relevant feature in E-value and .
- Organize the observation with a stable evidence ID.
- Apply this rule: A decision is stronger when the test fits the question and its limits are known.
- Choose the option the evidence supports and state the limit of the conclusion.
Real biomedical example: Two hits both show 99 , but one matched your whole sequence and the other matched only a tiny piece. Which one is the real ID of your , and how do the numbers prove it?
What the evidence supports: E1-E3 and F1 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 exact order of the four bases (adenine, thymine, guanine, cytosine) along a strand of DNA, which spells out genetic instructions.
- • PCR: Polymerase chain reaction, a lab technique that uses heat cycles and an to make millions of copies of a chosen DNA segment.
- • : A DNA reading method that uses chain-terminating dideoxynucleotides to make fragments of every length, then sorts them by size to reveal the base order.
- • : A search tool (Basic Local Search Tool) that compares a DNA or sequence against a database to find similar sequences and likely relatives.
- • E-value: In a search, a number estimating how many matches that strong you would expect by chance alone, so a smaller E-value means a more meaningful hit.
- • : In a sequence search, the percentage of your input sequence that lines up with a database match, showing how much of it was compared.
- • control: The comparison condition that isolates the effect of the variable being tested by keeping everything else the same.
Use it now: Choose one decision option. Cite E1 and E3, then explain how the rule connects the evidence to your choice.
Go further, optional: The source links below are optional enrichment. Every fact required for today's local evidence decision appears in this lesson package.
E-value is the expected number of matches that random chance would produce; a smaller E-value means the match is less likely to be coincidence.
Limit: E1 supplies context or an observation; it does not by itself establish the explanation.
A short region can match by chance, so a trustworthy identification needs high , a low E-value, and high together, because any one number alone can be fooled.
Limit: E2 is a teaching statement or comparison and must be checked against the task evidence.
You will be able to explain what E-value and measure.
Limit: E3 supports only the result or product criterion named here; it cannot justify a broader clinical or causal claim.
PLTW-GEND-2026-09-11 · Simulated classroom evidence scenario
Your role: medical interventions team member
Decision: Your team must decide what the evidence from E-value and supports before submitting the labeled and result claim named on the lesson page.
- • Select the option best supported by E1-E3.
- • Select a reasonable alternative and name the evidence it would require.
- • Delay the claim because the evidence does not distinguish the options.
Response: State one choice, cite at least two evidence IDs, explain the rule that connects them, and add one limitation. Submit it as the labeled and result claim.
Claim ceiling: The supplied lesson evidence can support an observation, pattern, classroom mechanism, or next-step decision about E-value and . It cannot by itself prove causation, establish a real clinical diagnosis, or justify action outside this classroom task.
Reason for review: Your team must decide what the evidence from E-value and supports before submitting the labeled and result claim named on the lesson page.
Context: A match is only as trustworthy as the evidence behind it: , E-value, and must agree before an identification can be believed.
- • T1: Reopen your results and find the E-value and for your top hit.
- • T2: Write what each means: E-value as how likely the match is by chance, coverage as how much aligned.
- • T3: Compare two hits and decide which is stronger using both numbers.
- • T4: Note the rule: a smaller E-value and higher coverage mean a more reliable match.
- • T5: Flag any hit that looks high in identity but low in coverage and explain the risk.
- • T6: Revise your identification statement to cite E-value and coverage.
- • E1: E-value is the expected number of matches that random chance would produce; a smaller E-value means the match is less likely to be coincidence.
- • E2: A short region can match by chance, so a trustworthy identification needs high , a low E-value, and high together, because any one number alone can be fooled.
- • E3: You will be able to explain what E-value and measure.
Measurements: Use only the measurements, units, graph, or counts supplied in today's task. No additional patient measurement is implied.
Figure finding: Teaching diagram for E-value and . Trace the labeled testing, treatment, or biological process and identify where evidence limits the decision. This is a teaching model, not patient or experimental data.
Uncertainty: This is a composite classroom scenario. Missing history, measurements, or confirmation tests remain unknown and limit the conclusion.
Mean = sum of values / number of values. Median = middle ordered value. Range = maximum - minimum.
For 2, 4, 4, and 10: mean = 20 / 4 = 5, median = 4, and range = 10 - 2 = 8.
Mean, median, and range keep the measurement unit. Order the values before finding the median.
Calculate the requested summary for today's supplied values, then write what it reveals and what it hides.
- • The solution must address the stated need in E-value and .
- • The decision must be supported by E1-E3.
- • The final product must make the success criteria visible.
- • Complete the work inside the 80-minute block.
- • Use only supplied or teacher-approved materials and evidence.
- • Do not trade , accessibility, or privacy for speed.
- • and evidence quality: must pass before scoring other criteria.
- • User need and effectiveness: highest scored criterion.
- • Time, cost, and ease of use: compare only after and effectiveness pass.
Test evidence: For each option, record the E1-E3 result that supports or fails each criterion. Do not assign a score without a named observation.
- Version or option tested
- Criterion met or missed
- Evidence ID and result
- Revision made
- Reason for the revision
- Need and user
- Criteria and constraints
- Chosen option and evidence
- Test result
- Revision and reason
Students often think Students believe high alone proves a match, so they ignore E-value and .. The trap: A short stretch can hit 99 by chance, so a high identity with low or a large E-value is unreliable, because you only compared a sliver of your sequence. Reading identity alone is exactly how a false match sneaks through.
Best match: Staphylococcus aureus.
I chose it because it has the lowest E-value (2e-145, which is far closer to zero than any other row), the highest query coverage (99%, so almost my whole sequence aligned), and the highest percent identity (99.4%). Staphylococcus epidermidis is close, but it is lower on all three numbers, so it is the second choice, not the call. Bacillus subtilis (E-value 0.8) and E. coli (E-value 4.5) have E-values near or above 1, which means a match that good could easily happen by chance, so they are not trustworthy identifications.
| Match | Query coverage | E-value | Identity |
|---|---|---|---|
| Staphylococcus aureus | 99% | 2e-145 | 99.4% |
| Staphylococcus epidermidis | 97% | 3e-120 | 94.1% |
| Bacillus subtilis | 41% | 0.8 | 78.0% |
| Escherichia coli | 22% | 4.5 | 71.2% |
This model shows the level of evidence and organization needed to complete: Completes the BLAST evidence step of the pathogen-ID investigation: a recorded results table plus a defended best-match call.
- Name the variables and include units.
- Enter observations without changing the raw values.
- Check labels, calculations, and patterns before interpreting the data.
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: Paste the screenshot of your BLAST hit table into your evidence log and write the one-sentence claim naming your pathogen.
- 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 E-value and query coverage. 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.
Classroom documents for this lesson are posted in Schoology. Open Clever, then Schoology, and find each one by the name shown on its card.
Open this when the class reaches this activity and use it to complete the required lesson artifact.
Placement rationale
Matched identification, PCR, sequencing, by path:Medical-Interventions/Unit-1_How-to-Fight-Infection/1.1_The-Mystery-Infection; keywords:blast, sequencing, pathogen, dna, identification. Score 162. Visibility: student-schoology (student-facing resource; link through Schoology rather than local path).
Use this after the required lesson work when you are ready for a harder application or a deeper connection.
Placement rationale
Matched identification, PCR, sequencing, by path:Medical-Interventions/Unit-1_How-to-Fight-Infection/00_Unit-Overview; keywords:blast, pathogen, dna, identification. Score 150. 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 identification, PCR, sequencing, by path:Medical-Interventions/Unit-1_How-to-Fight-Infection/00_Unit-Overview; keywords:blast, pcr, pathogen, identification. Score 150. Visibility: student-schoology (student-facing resource; link through Schoology rather than local path).
How to get there: open Clever and sign in with your Microsoft (district) account. Both myPLTW and Schoology are in Clever. Do the activity in myPLTW. Turn the work in on this site or hand it to Mr. Mendoza, because that is the step that counts as submitted. Schoology only shows your report-card grade later.
Check yourself · commit, then reveal▸
Claim ceiling for this check: The supplied lesson evidence can support an observation, pattern, classroom mechanism, or next-step decision about E-value and . It cannot by itself prove causation, establish a real clinical diagnosis, or justify action outside this classroom task.
Hit A: 99% identity, E-value 2e-60, query coverage 98%. Hit B: 99% identity, E-value 0.4, query coverage 11%. Which is the more trustworthy identification, and why?
Write an answer and pick a confidence to unlock the key.
Fast retrieval with instant answers, not the commit-then-reveal check above. Try each from memory first: write what you remember about the earlier units, then check yourself here.
Go further and get help▸
I can name the procedure's purpose and the evidence I will record. I can identify each named hazard and the control that reduces it: Wear the required PPE, keep the bench clear, handle equipment only as directed, and know where the eyewash, sink, and spill kit are before you start. My data table is ready before materials are handled.
Finish the checklist before you handle any material.
- • Wear the required PPE, keep the bench clear, handle equipment only as directed, and know where the eyewash, sink, and spill kit are before you start.
- • Human samples and data stay private: label with a code, never a name, and dispose of materials in the correct waste container, then wash your hands.
- 1Before materials are handled, identify the purpose, variables or comparison, controls, measurement units, and stop-work condition.
- 2Reopen your BLAST results and find the E-value and query coverage for your top hit.
- 3Write what each means: E-value as how likely the match is by chance, coverage as how much aligned.
- 4Compare two hits and decide which is stronger using both numbers.
- 5Note the rule: a smaller E-value and higher coverage mean a more reliable match.
- 6Flag any hit that looks high in identity but low in coverage and explain the risk.
- 7Revise your pathogen identification statement to cite E-value and coverage.
- 8Record each result in the prepared table before interpreting it. Mark missing, repeated, or invalid results truthfully.
- 9Complete the named cleanup and waste route, remove PPE safely, wash hands when required, and confirm the station is ready for the next group.
| Trial or sample ID | Independent condition | Measured result with units | Observation before interpretation | Quality-control note |
|---|---|---|---|---|
Before the procedure, predict the result and cite the rule behind the prediction.
After the procedure, compare the result with the prediction and name one limitation or source of uncertainty.
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.
Today is individual work you can do from home: complete the same target above, then submit your Data table.
Open the drop folderTurn this in at the drop folder with your district Microsoft sign-in, or hand it to Mr. Mendoza in class. Both count as submitted. Doing the activity in myPLTW does not.
Class still runs. Complete the online activity above (it's self-guided). Need the concept taught without a teacher? Use this authoritative explainer:
NCBI BLAST- 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, on the class site or handed to Mr. Mendoza in class, and confirmed. Not in Schoology: that is where the report-card grade appears later.
- Error analysis and method · counts doubleName a specific limit of the method and how it moved your result, and compare what you predicted to what happened. "Human error" does not count; say what about the procedure or instrument caused it.