Wildtype One
@wildtypeone.bsky.social
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Finally, the love child of AI and microscopy.
A major advance.
Thanks for sharing @kevin-dean.bsky.social
A major advance.
Thanks for sharing @kevin-dean.bsky.social
November 12, 2025 at 7:31 AM
Finally, the love child of AI and microscopy.
A major advance.
Thanks for sharing @kevin-dean.bsky.social
A major advance.
Thanks for sharing @kevin-dean.bsky.social
Deep learning meets mass spec — the collab we’ve been waiting for
Nice work Mann Lab 🫡 and thanks for sharing @mannlab.bsky.social
Nice work Mann Lab 🫡 and thanks for sharing @mannlab.bsky.social
November 11, 2025 at 6:54 PM
Deep learning meets mass spec — the collab we’ve been waiting for
Nice work Mann Lab 🫡 and thanks for sharing @mannlab.bsky.social
Nice work Mann Lab 🫡 and thanks for sharing @mannlab.bsky.social
Fan sounds like a jet but she’s fighting for her life 💨🥵
November 11, 2025 at 6:51 PM
Fan sounds like a jet but she’s fighting for her life 💨🥵
Love the comprehensive multi-omics approach. Interesting to see female patients showing stronger neuroinflammatory and pro-inflammatory signatures.
Long COVID isn’t one disease, it’s a whole ecosystem of chaos.
Thanks for sharing @castltrastondrs.bsky.social
Long COVID isn’t one disease, it’s a whole ecosystem of chaos.
Thanks for sharing @castltrastondrs.bsky.social
November 10, 2025 at 7:28 AM
Love the comprehensive multi-omics approach. Interesting to see female patients showing stronger neuroinflammatory and pro-inflammatory signatures.
Long COVID isn’t one disease, it’s a whole ecosystem of chaos.
Thanks for sharing @castltrastondrs.bsky.social
Long COVID isn’t one disease, it’s a whole ecosystem of chaos.
Thanks for sharing @castltrastondrs.bsky.social
Great work—both the technique and the model you proposed are like chromatin folding in 4K resolution 📸
Thanks for sharing, @jojdavies.bsky.social
Thanks for sharing, @jojdavies.bsky.social
November 10, 2025 at 7:25 AM
Great work—both the technique and the model you proposed are like chromatin folding in 4K resolution 📸
Thanks for sharing, @jojdavies.bsky.social
Thanks for sharing, @jojdavies.bsky.social
🧫 Join 500+ elite researchers getting weekly lab hacks with our newsletter (it’s free) 👉 wildtypeone.substack.com/about
November 10, 2025 at 7:21 AM
🧫 Join 500+ elite researchers getting weekly lab hacks with our newsletter (it’s free) 👉 wildtypeone.substack.com/about
We chose to pair the samples because they were treated equally along the way
This eliminates variability
The two conditions are very close that they mimic a paired set
Happy analyzing!
— Wildtype One 🧬
(8/8)
This eliminates variability
The two conditions are very close that they mimic a paired set
Happy analyzing!
— Wildtype One 🧬
(8/8)
November 10, 2025 at 7:20 AM
We chose to pair the samples because they were treated equally along the way
This eliminates variability
The two conditions are very close that they mimic a paired set
Happy analyzing!
— Wildtype One 🧬
(8/8)
This eliminates variability
The two conditions are very close that they mimic a paired set
Happy analyzing!
— Wildtype One 🧬
(8/8)
Examples:
• "Treated" and "Control" were seeded from the same batch of cells, then plated and harvested together
• "Treated" and "Control" are two wells on the same plate
Why choose paired here?
(7/8)
• "Treated" and "Control" were seeded from the same batch of cells, then plated and harvested together
• "Treated" and "Control" are two wells on the same plate
Why choose paired here?
(7/8)
November 10, 2025 at 7:20 AM
Examples:
• "Treated" and "Control" were seeded from the same batch of cells, then plated and harvested together
• "Treated" and "Control" are two wells on the same plate
Why choose paired here?
(7/8)
• "Treated" and "Control" were seeded from the same batch of cells, then plated and harvested together
• "Treated" and "Control" are two wells on the same plate
Why choose paired here?
(7/8)
⚠️ If your conditions were run in parallel. Or the "treated" and "control" were somehow attached. They might look unpaired on paper. But when you run statistics, you have to pair them!
Here are examples:
...
(6/8)
Here are examples:
...
(6/8)
November 10, 2025 at 7:19 AM
⚠️ If your conditions were run in parallel. Or the "treated" and "control" were somehow attached. They might look unpaired on paper. But when you run statistics, you have to pair them!
Here are examples:
...
(6/8)
Here are examples:
...
(6/8)
Here, each subject serves as its OWN control. Each has its own variability.
A paired test gives you more statistical power.
⚠️ But there are important exceptions:
(5/8)
A paired test gives you more statistical power.
⚠️ But there are important exceptions:
(5/8)
November 10, 2025 at 7:18 AM
Here, each subject serves as its OWN control. Each has its own variability.
A paired test gives you more statistical power.
⚠️ But there are important exceptions:
(5/8)
A paired test gives you more statistical power.
⚠️ But there are important exceptions:
(5/8)
⛓️ Choose “paired” when…
Measurements come from the same subject under different conditions.
• Classic example: Measuring heart rate before vs. after drinking coffee. Same person
• Example 2: Monitoring tumor volume before and after drug treatment. Repeated measures
(4/8)
Measurements come from the same subject under different conditions.
• Classic example: Measuring heart rate before vs. after drinking coffee. Same person
• Example 2: Monitoring tumor volume before and after drug treatment. Repeated measures
(4/8)
November 10, 2025 at 7:18 AM
⛓️ Choose “paired” when…
Measurements come from the same subject under different conditions.
• Classic example: Measuring heart rate before vs. after drinking coffee. Same person
• Example 2: Monitoring tumor volume before and after drug treatment. Repeated measures
(4/8)
Measurements come from the same subject under different conditions.
• Classic example: Measuring heart rate before vs. after drinking coffee. Same person
• Example 2: Monitoring tumor volume before and after drug treatment. Repeated measures
(4/8)
This applies to:
• Unpaired t-test (for two groups)
• Ordinary one-way ANOVA (for >2 groups)
Unpair them when each data point is from a different, unrelated subject
(3/8)
• Unpaired t-test (for two groups)
• Ordinary one-way ANOVA (for >2 groups)
Unpair them when each data point is from a different, unrelated subject
(3/8)
November 10, 2025 at 7:18 AM
This applies to:
• Unpaired t-test (for two groups)
• Ordinary one-way ANOVA (for >2 groups)
Unpair them when each data point is from a different, unrelated subject
(3/8)
• Unpaired t-test (for two groups)
• Ordinary one-way ANOVA (for >2 groups)
Unpair them when each data point is from a different, unrelated subject
(3/8)
⛓️💥 Choose an “unpaired” test when…
The two groups you’re comparing are independent.
• Example 1: Comparing protein expression in treated vs. control cells
• Example 2: Comparing tumor sizes in mice Group A vs. Group B
Each sample is separate. Different subjects.
(2/8)
The two groups you’re comparing are independent.
• Example 1: Comparing protein expression in treated vs. control cells
• Example 2: Comparing tumor sizes in mice Group A vs. Group B
Each sample is separate. Different subjects.
(2/8)
November 10, 2025 at 7:17 AM
⛓️💥 Choose an “unpaired” test when…
The two groups you’re comparing are independent.
• Example 1: Comparing protein expression in treated vs. control cells
• Example 2: Comparing tumor sizes in mice Group A vs. Group B
Each sample is separate. Different subjects.
(2/8)
The two groups you’re comparing are independent.
• Example 1: Comparing protein expression in treated vs. control cells
• Example 2: Comparing tumor sizes in mice Group A vs. Group B
Each sample is separate. Different subjects.
(2/8)
November 9, 2025 at 5:17 PM
Reposted by Wildtype One
Once again, I beg you to understand that SINGLE-CHANNEL FLUORESCENCE MICROSCOPY IMAGES DON'T HAVE A COLOR!
November 9, 2025 at 3:13 PM
Once again, I beg you to understand that SINGLE-CHANNEL FLUORESCENCE MICROSCOPY IMAGES DON'T HAVE A COLOR!
Thanks for sharing @drmikewoerdemann.bsky.social !
November 9, 2025 at 5:15 PM
Thanks for sharing @drmikewoerdemann.bsky.social !