Bat Immunological Training Education (BITE) outreach at Discovery Place yesterday.
We had 171 visitors at our booths today. We will continue to educate the public about diseases and immune responses.
At Discovery Place every 3rd Saturday of the month. #microsky #bats #Stem
Great job team!
Thank you brother! Exactly 💯 correct! That's why I built it this way! You get analysis of MetaCerberus -> pyGAGE -> Pathview-plus -> think = pubs.
If you’re already doing differential expression in Python:
This drops in directly.
No exporting. No context switching.
That alone saves time!!
ALSO outputs feed pathview-plus our pathway tool!
pip install pygage
pip install pathview-plus
#Bioinformatics #rnaseq #computationalbiology
Where this shines:
• small RNA-seq studies (n < 5/group)
• fast exploratory analysis
• pipeline integration (pandas/NumPy workflows)
Basically: real-world data!!
Limitations (important):
• ignores gene–gene correlation
• pathway size affects variance
Not perfect.
But the tradeoff → speed + stability is often worth it.
But that is corrected in our pathway level tool -> pathview-plus when you feed pyGAGE outputs to it!!
Hot take:
Most people don’t need more advanced enrichment methods!
They need ones they’ll actually run.
#rnaseq #bioinformatics #computational
Under the hood:
For a gene set S:
→ compute mean(d_g)
→ build null by sampling random gene sets of same size
→ compute Z-score vs that null
No permutations. No heavy compute.
This is why it’s fast!
Its not analysis that takes long - its testing 50 tools that don't run to get some data back!!
8/ It’s not the fanciest method.
But it actually works in real pipelines.
And now it works natively in Python.
#bioinformatics #rnaseq #genomics
7/ Output:
• Z-scores
• up/down pathway direction
• FDR-corrected significance
Fast, interpretable, reproducible!
Now and today!!
6/ pyGAGE avoids that.
Gene randomization → stable inference even at low sample size
5/ That last part matters.
Most methods rely on sample permutation.
That breaks when n is small (which is most datasets).
4/ The method is simple and solid:
→ compute gene-level differential signal
→ aggregate into pathways
→ compare to a null via gene randomization
3/ So I built pygage — a Python implementation of GAGE.
No bridges. No friction. Just runs.
2/ Gene-level stats ≠ biological interpretation.
You need pathway-level signals.
That’s where gene set enrichment comes in.
But most tools are:
• slow
• fragile with small n
• stuck in R
Most RNA-seq pipelines are doing this wrong.
They run differential expression…
and stop there.
You’re leaving biological signal on the table.
I built pygage to fix that 👇
pip install pygage
#Bioinformatics #rnaseq #computation #computationalbiology
🔬 Pathview-plus = powerful pathway visualization for bioinformatics 🚀
Thousands of pathway maps (KEGG + SBGNview) and super easy to use.
Install in seconds:
pip install pathview-plus
GitHub: github.com/raw-lab/path...
PyPI: pypi.org/project/path...
#Bioinformatics #DataScience #Omics
They should be careful with the word dormancy. Not quite the same things.
Send us a mail. We are always developing it.
Works well for bacteria as well in mixtures with viruses.
The first automated computer vision–based software enabling the detection, enumeration, and sizing of virus-like particles from epifluorescence microscopy (EFM) images of environmental samples.
Published online in BMC methods today. #giantvirus #phagesky
Paper
link.springer.com/article/10.1...
@bhuwanabbot.bsky.social @morgancarterphd.bsky.social @raw937.bsky.social @andrabuchan.bsky.social et al. present a pangenome analysis of the endofungal genus Mycetohabitans, showing bacteria-fungus coevolution.
🔗 doi.org/10.1093/gbe/evaf231
#genome #evolution #pangenome #MicrobeSky
May the phage be with you!
Bat Immunological Training Education (BITE) outreach at Discovery Place yesterday.
We had 324 visitors at our booths today. We will continue to educate the public about diseases and immune responses.
At Discovery Place every 3rd Saturday of the month. #microsky #bats
Great job team!
Awesome work. With some phageyness at the end. #phage #phagesky #microsky #evolution
Wonderful paper, amazing work, wonderful lab, and amazing collaborators!! Well done Morgan!!
Latest in our #Phage collection
Through #experimentalevolution, researchers at @ucsandiego.bsky.social trained #phages to increase their ability to inhibit multidrug-resistant and extensively drug-resistant Klebsiella pneumoniae 🧫
@natcomms.nature.com
www.nature.com/articles/s41...
We were glad to work on the data! ;-)
Thanks for the repost