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#singlecell

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Christian Mayer

Now out in #NatureNeuroscience: "Temporal control of progenitor competence shapes maturation in GABAergic neuron development in mice".

Congrats to first authors Ann Bright, Yana Kotlyarenko, Florian Neuhaus — and thanks to all collaborators!

nature.com/articles/s41593-025

#NewsMayerlab #NeuroFediverse #SingleCell #DevelopmentalBiology

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NatureTemporal control of progenitor competence shapes maturation in GABAergic neuron development in mice - Nature NeuroscienceUnlike cortical progenitors, ventral telencephalic progenitors retain the ability to generate diverse neuron types during neurogenesis. Here, the authors show that ventral telencephalic progenitor maturation is gated by developmental timing, revealing a distinct regulatory logic underlying the development of inhibitory neurons.
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Alberto Perez-Posada

Happy to see out our latest work on studying animal body size variations using single cell transcriptomics to measure gene expression of individual cells. Learned my fair bit of statistics here, and most importantly I learned how to build wrapper functions for "complex" tasks in R (such as differntial gene expression) in a modular way. Thanks to all the authors involved! science.org/doi/10.1126/sciadv #singlecell #scrna #allometry #splitseq #planarians #generegulation

Center for Health Data Science

🔬✨Zooming In—One Cell at a Time!

The 5th Danish #Single-Cell #Symposium is coming to #Copenhagen, and it's THE place to be if you’re into all things single-cell!

Topics will include:
Advances in single-cell #genomics and #transcriptomics
#Computational approaches to #dataanalysis
Applications in health and disease

🗓️May 15–16
📍Hosted at Panum, UCPH
💡Scientists, students, and techies are all welcome!

🔗 Check it out: events.au.dk/5thdanishsingle-c

#SingleCell#ScienceInCopenhagen#LifeScience
Replied in thread
Ming 'Tommy' Tang

8/ Objects make it easy to organize and understand all the data we need for analysis! Just like your body and phone organize the things inside them. #OOP #Bioinformatics #SingleCell #Seurat read my blog post on a simple example in R divingintogeneticsandgenomics.

Chatomics · S3 and S4 objects in R explained | ChatomicsIn R, S3 and S4 objects are related to object-oriented programming (OOP), which allows you to create custom data structures with associated behaviors and methods. Let me explain them using simple language and metaphors, along with practical examples. S3 Objects Imagine you have a collection of toys, like cars, dolls, and action figures. Each toy has its own set of properties (color, size, material) and behaviors (move, make sounds, etc.
Eli Roberson (he/him)

#Genomics #SingleCell

These FASTQ files are driving me batty.

I have FASTQ files for a Chromium prepared library. I run cutadapt to try and limit bad reads. I run RNASTAR solo with correct parameters to extract the read UMI and GEM barcode into UM CB tags of BAM file.

I run umitools to dedup based on barcode.

AssertionError: not all umis are the same length(!): 1 - 10

Why. Is umitools. Dying??? All the barcodes and UMIs should be the same length. They're fixed length pulls from the read.

Eli Roberson (he/him)

Any #rstats #Genomics #SingleCell people used scSplit for genetic demultiplexing of non-hashed mixed samples?

On the GitHub page it says:

"If necessary, remove duplicated reads based on UMI using tools like rmdup in UMI-tools."

github.com/jon-xu/scSplit

That makes sense. But shouldn't it really be by GEM *and* UMI? Just UMI would mix GEMs, and that would exclude identically mapping reads from different droplets. Unless umitools checks *both*. I've only used it on fastq files before, not BAM.

GitHubGitHub - jon-xu/scSplit: Genotype-free demultiplexing of pooled single-cell RNA-Seq, using a hidden state model for identifying genetically distinct samples within a mixed population.Genotype-free demultiplexing of pooled single-cell RNA-Seq, using a hidden state model for identifying genetically distinct samples within a mixed population. - jon-xu/scSplit
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