#scRNAseq

2026-01-20

Our new pre‑print is out!

scReady – an automated and accessible pipeline for single‑cell RNA‑Seq preprocessing: Empowering novice bioinformaticians

wellcomeopenresearch.org/artic

@haessar.bsky.social @fionan-a.bsky.social @yiyicheng

#scRNAseq #bioinformatics

2025-09-02

Pipeline release! nf-core/scnanoseq v1.2.1 - nf-core/scnanoseq v1.2.1 - Zinc Turtle!

Please see the changelog: github.com/nf-core/scnanoseq/r

#10xgenomics #longreadsequencing #nanopore #scrnaseq #singlecell #nfcore #openscience #nextflow #bioinformatics

2025-07-31

#NeuralStemCells (NSCs) & ependymal cells (ECs) are derived from #RadialGlialCells. This study uses #scRNAseq to characterize cell fate trajectories in the developing #VentricularZone, identifying TFEB as a regulator of the NSC/EPC balance @PLOSBiology plos.io/3HbrsJG

Top: CD133 showed specific enrichment on the apical surface of radial glial cells (RGCs) in the developing ventricular zone (VZ) from postnatal day 0 (P0) to P15. Ciliary membrane marker (ARL13B) and the ciliary microtubule marker acetylated-tubulin (ac-TUB) indicated ependymal cell (EPC)-lineage differentiation. Cell proliferating marker (Ki67) and neural stem cell (NSC)-lineage marker (ASCL1) indicated NSC-lineage transition. The framed region was further magnified to show details. The boundary between lateral ventricle (LV) and VZ was denoted by the yellow dotted line for better distinguishing ciliary ac-TUB and cytoplasmic ac-TUB in (B). The scale bars are 20 μm. Bottom: A model illustrating how TFEB functions in the process of bGPC specification during VZ development.
Marc Robinson-Rechavimarcrr@ecoevo.social
2025-07-23

Yuyao Song presents ScGOclust to compare #singlecell #scRNAseq between distant species, such as fly and mammal: gene level comparisons don’t work because there has been too much divergence. 💡 Instead of genes, use GO terms has features to compare cells. #ismbeccb2025
doi.org/10.1093/bioinformatics

Daniel Hoffmann 🌼Daniel_Hoffmann@mathstodon.xyz
2025-06-13

Single cell RNA-sequencing (#scRNAseq) is an essential method to learn about cells in health and disease. Here we have studied "multiplets", an important source of error of scRNAseq. We find that multiplets are astonishingly frequent and hard to eliminate.
doi.org/10.1101/2025.06.09.658

2025-06-09

Pipeline release! nf-core/scnanoseq v1.2.0 - nf-core/scnanoseq v1.2.0 - Copper Rhinoceros!

Please see the changelog: github.com/nf-core/scnanoseq/r

#10xgenomics #longreadsequencing #nanopore #scrnaseq #singlecell #nfcore #openscience #nextflow #bioinformatics

2025-04-30

How do #brain cells change over #evolution? @bentonlab compare #scRNAseq from ecologically distinct #drosophilid species to identify changes in composition & gene expression of different cell types, revealing higher divergence in #glia than #neurons @PLOSBiology plos.io/4js7Rms

Single-nucleus transcriptomic atlases of D. melanogaster, D. simulans, and D. sechellia central brains. Top left: phylogeny of the drosophilid species studied in this work, and images of reference central brains for these species (all female). Top right: Workflow of the single-nucleus RNA-sequencing of drosophilid central brains. Bottom left: tSNE plots of D. melanogaster (red), D. simulans (green) and D. sechellia (blue) central brain cells from an integrated dataset after RPCA integration. In the bottom right plot, all cells from the three species are merged. Bottom right: tSNE plot of the integrated and annotated datasets. Cells are colored by the 11 annotation groups. Unannotated cells are colored gray.
2025-04-23

How does transcriptional patterning regulate #SalivaryGland #morphogenesis? Annabel May & @katjaroeper use #scRNAseq of early morphogenesis of the #Drosophila salivary gland placode to reveal regulation by induction & exclusion of regulatory factors @PLOSBiology plos.io/4cUw827

Top: Immunofluorescence images and matching schematics of the anterior ventral half of Drosophila embryos at the indicated stages, highlighting the cells of the salivary gland placode, labelled with fkhGal4 x UAS-srcGFP. All cell outlines are labeled for phosphotyrosine to label adherens junctions (PY20, magenta) and srcGFP is in green, the stage 10 panel is shown with increased exposure, other panels are identical exposure. Scale bar is 100µm. Middle panels are matched schematics, showing the position of the salivary gland placode in pale green, the area of initial apical constriction in bright green and the forming invagination pit in black. Lower panels show schematics of cross sections (positioned indicated by magenta dotted lines in middle panels) of the invaginating tube. Bottom: A salivary gland placode in the Drosophila embryo at the onset of tube morphogenesis, labelled for four jointed (fj)  (cyan) and fkh (magenta) expression by HCR and with cell outlines labelled by PY-20, detecting phospho-tyrosine at adherens junctions (yellow).
Nicola Romanònicolaromano@qoto.org
2025-04-07

Our new preprint is now out!

Dynamic transcriptional heterogeneity in pituitary corticotrophs

biorxiv.org/content/10.1101/20

We analysed publicly available single-cell RNA sequencing data of pituitary gland tissue and looked at corticotrophs, cells that are central to mediate stress responses.

We identified several transcriptional states in these cells that are related to how they respond to stress. Cells are able to transition between these states and this might be helpful for them to respond to stress coming at unpredictable times.

We also highlight issues related to using scRNAseq to look at functional subpopulations of cells.

#scrnaseq #stress #physiology #cellbiology #bioinformatics #corticotrophs #pituitary

2025-03-18

Pipeline release! nf-core/scnanoseq v1.1.0 - nf-core/scnanoseq v1.1.0 - Iron Alligator!

Please see the changelog: github.com/nf-core/scnanoseq/r

#10xgenomics #longreadsequencing #nanopore #scrnaseq #singlecell #nfcore #openscience #nextflow #bioinformatics

2024-12-30

mascarade package implements a procedure to automatically generate 2D masks for clusters on single-cell dimensional reduction plots like t-SNE or UMAP github.com/alserglab/mascarade #rstats #scRNAseq

2024-12-10

chatomics! How to Fine-Tune the Best Clustering Resolution for #scRNAseq Data 🎯 🧵

2024-11-28

Finally, our paper studying synovial tissue #DC #DendtriticCells in joint health and #rheumatoidArthritis is out in Immunity!
#scRNAseq #spatialTranscriptomic
From: @ImmunityCP
mstdn.science/@ImmunityCP/1135

Daniel Hoffmann 🌼Daniel_Hoffmann@mathstodon.xyz
2024-11-21
Daniel Hoffmann 🌼Daniel_Hoffmann@mathstodon.xyz
2024-11-18
2024-11-13

Insbesondere bei der Interpretation von #RNA-Sequenzanalysen einzelner Zellen (#scRNAseq) sind Techniken zur Dimensionen-Reduktion wie #UMAP der neuste Schrei. Doch bilden UMAP-Plots tatsächlich die Realität ab? Es gibt Zweifel … Zur Methoden-Kontroverse: laborjournal.de/rubric/hinterg

Comiczeichnung eines jungen Forschers, der jubelnd einen ausgedruckten UMAP-Plot über den Kopf hält. Dahinter fasst sich eine junge Kollegin mit geschlossenen Augen konsterniert an die Stirn. Um das Bild fließt teilweise angeschnittener Text des zugehörigen Artikels. Links oben Dachzeile "Methoden-Kontroverse" und Überschrift "UMAP – Die Antwort auf alle Fragen?", darunter der Vorspann und beginnender Fließtext.
Regenerative Research Fdn/NSCINeuralStemCells@mstdn.science
2024-10-22

🔊 New pre-print from David Butler and team!
"HSV-1 Infection Alters MAPT Splicing and Promotes Tau Pathology in Neural Models of Alzheimer's Disease"
#organoid #tauopathy #neurodegeneration #scRNAseq #Neuracell

biorxiv | zurl.co/iWU1

2024-10-11

An interesting bioRxiv preprint was shared on the 🐦 site (x.com/strnr/status/18441056669). The paper describes a model to represent cells from large scale scRNA seq atlases using LLMs. Apart from the novelty value one of the main draws should be the ability to map any dataset with no additional data labelling, model training or fine-tuning onto the existing universal cell embedding. biorxiv.org/content/10.1101/20
github.com/snap-stanford/UCE
#scRNAseq #embedding #biology #llm

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