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Ming Tommy Tang @tommytang.bsky.social · 25m

A secure web-based, collaborative terminal sshx.io/ might be good for teaching

Ming Tommy Tang @tommytang.bsky.social · 55m

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Hi! I'm Tommy Tang

I am a bioinformatician/computational biologist with six years of wet lab experience and over 12 years of computation experience. I will help you to learn computational skills to tame astronomical data and derive insights. Check out the resources I offer below and sign up for my newsletter!

divingintogeneticsandgenomics.ck.page

Ming Tommy Tang @tommytang.bsky.social · 55m

11/
Full 10x tech note on introns:
assets.ctfassets.net/an68im79xit...
If you see intronic reads in your UMI matrix—don’t panic.
They’re part of the story.
Let your data tell it.

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Ming Tommy Tang @tommytang.bsky.social · 55m

10/
Key Takeaways
Intronic reads in 10x 3′ data are normal

Caused by internal poly-A priming & pre-mRNA capture

They enhance sensitivity, not noise

<0.1% gDNA contamination

Use introns unless you have a reason not to

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Ming Tommy Tang @tommytang.bsky.social · 55m

9/
You Still Have Control
Don’t want introns?
Cell Ranger 7.0+ includes them by default.
Use --gex-exclude-introns to disable if needed
Just know that excluding them = lower detection rates.

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Ming Tommy Tang @tommytang.bsky.social · 55m

8/
Impact on Downstream Analysis?
Almost none.
Using introns still retains 97.27% clustering agreement with exon-only analysis in PBMCs
You won’t distort your results—but you’ll gain sensitivity.

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Ming Tommy Tang @tommytang.bsky.social · 55m

7/
Strand Invasion During Reverse Transcription
Poly(dT) primers can bind to the cDNA itself during RT.
This can result in “self-primed” captures of intronic fragments
Yes—it’s weird. But it’s real.

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Ming Tommy Tang @tommytang.bsky.social · 55m

6/
Longer Genes = More Introns = More Signal
There’s a gene-length bias.
Longer transcripts naturally have more internal poly-A sequences.
So introns in long genes are more likely to get captured.

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Ming Tommy Tang @tommytang.bsky.social · 55m

5/
Still Worried About Genomic DNA?
Don’t be.
Less than 0.1% of UMIs are from gDNA
That’s negligible.
The intronic signal is from real RNA, not DNA contamination.

1

Ming Tommy Tang @tommytang.bsky.social · 55m

4/
What You Gain with Introns
Including intronic reads increases:
+59% median genes per cell

+48% total UMI counts

Detection of genes with no exonic reads

That’s more power, not more noise.

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Ming Tommy Tang @tommytang.bsky.social · 55m

3/
Pre-mRNA Is Everywhere—Especially in Nuclei
When working with nuclear RNA, unspliced pre-mRNA dominates.
Result?
34–58% of UMIs map to introns in nuclei samples
And that’s not bad—it boosts sensitivity.

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Ming Tommy Tang @tommytang.bsky.social · 55m

2/
Internal Poly-A Priming
Poly(dT) primers don’t only bind the 3′ poly-A tail.
They sometimes bind internal poly-A stretches in introns—especially in pre-mRNA.
Introns have ~21× more poly-A 7-mers than exons

1

Ming Tommy Tang @tommytang.bsky.social · 55m

1/
Yes, 10x 3′ single-cell RNA-seq targets poly-A tails.
So why are 30–50% of reads mapping to introns?
Because of both biology and tech.
You’re not doing it wrong.

1

Ming Tommy Tang @tommytang.bsky.social · 55m

You’re analyzing 10x Genomics single-cell RNA-seq and notice lots of intronic reads.
Wait—wasn’t this a 3′ UMI-based assay for mature mRNA?
Let’s unpack why introns show up—and why they matter. 🧵

1

Ming Tommy Tang @tommytang.bsky.social · 23h

The genomic landscape of relapsed infant and childhood KMT2A-rearranged acute leukemia www.nature.com/articles/s4...

3

Ming Tommy Tang @tommytang.bsky.social · 1d

I hope you've found this post helpful.

Follow me for more.

Subscribe to my FREE newsletter chatomics to learn bioinformatics divingintogeneticsandgenomics.ck.page/profile

Hi! I'm Tommy Tang

I am a bioinformatician/computational biologist with six years of wet lab experience and over 12 years of computation experience. I will help you to learn computational skills to tame astronomical data and derive insights. Check out the resources I offer below and sign up for my newsletter!

divingintogeneticsandgenomics.ck.page

Ming Tommy Tang @tommytang.bsky.social · 1d

14/14
Bioinformatics isn’t just code.
It’s systems engineering in disguise.
Every error conquered = deeper understanding.
You’ve got this. 💪

1

Ming Tommy Tang @tommytang.bsky.social · 1d

13/14
Key Takeaways:
Red text = clues, not failure

90% of errors are missing system libs

Isolate issues with clean environments

Document every fix—you’ll forget

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Ming Tommy Tang @tommytang.bsky.social · 1d

12/14
Windows users:
Install Rtools for C/C++ dependencies:
cran.r-project.org/bin/windows...

Restart RStudio after installing!

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Ming Tommy Tang @tommytang.bsky.social · 1d

11/14
Permission denied?
Never use sudo R. Instead:

install.packages("pkg", lib="~/R/libs") # User directory

Add export R_LIBS_USER=~/R/libs to .bashrc.

1

Ming Tommy Tang @tommytang.bsky.social · 1d

10/14
Nuclear option: Start fresh.

R --vanilla # No startup configs
install.packages("problematic_pkg")

Or use renv/conda for isolated environments.

1

Ming Tommy Tang @tommytang.bsky.social · 1d

9/14
ChatGPT Prompt Template:
"I’m on macOS Ventura, R 4.3.0. Trying to install DESeq2 with BiocManager::install(). Got this error: [paste]. Whats wrong?
Context matters.

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Ming Tommy Tang @tommytang.bsky.social · 1d

8/14
Still stuck?
Google the exact error in quotes:
"error: X11 headers not found" site:stackoverflow.com (you search with that site! cool google trick).
Add R or Bioconductor to narrow results.

Newest Questions

Stack Overflow | The World’s Largest Online Community for Developers

stackoverflow.com

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Ming Tommy Tang @tommytang.bsky.social · 1d

7/14
Bioconductor packages: Always use:
BiocManager::install("limma") # Not install.packages()!

Bioconductor has its own dependency tree.

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Ming Tommy Tang @tommytang.bsky.social · 1d

6/14
Installing Seurat? Common error:
libgfortran.so.3: cannot open...
Linux:
sudo apt install libgfortran3

macOS:
brew install gcc # Installs Fortran libs

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