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#Transcriptomics

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"Whole-embryo Spatial Transcriptomics at Subcellular Resolution from Gastrulation to Organogenesis", by Wan et al. 2024
biorxiv.org/content/10.1101/20

bioRxiv · Whole-embryo Spatial Transcriptomics at Subcellular Resolution from Gastrulation to OrganogenesisSpatiotemporal patterns of gene expression underlie embryogenesis. Despite progress in single-cell genomics, mapping these patterns across whole embryos with comprehensive gene coverage and at high resolution has remained elusive. Here, we introduce a whole-embryo imaging platform using multiplexed error-robust fluorescent in-situ hybridization (weMERFISH). We quantified the expression of 495 genes in whole-mount zebrafish embryos at subcellular resolution. Integration with single-cell multiomics data generated an atlas detailing the expression of 25,872 genes and the accessibility of 294,954 chromatin regions, explorable with an online interface MERFISHEYES (beta version). We found that temporal gene expression aligns with cellular maturation and morphogenetic movements, diverse expression patterns correspond to composites of tissue-specific accessible elements, and changes in gene expression generate sharp boundaries during gastrulation. These results establish a novel approach for whole-organism spatial transcriptomics, provide a comprehensive spatially resolved atlas of gene expression and chromatin accessibility, and reveal the diversity, precision and emergence of embryonic patterns. ### Competing Interest Statement The authors have declared no competing interest.

STATGEN 2024 talk
Statistical Methods for Single-Cell RNA-Seq Analysis and Spatial Transcriptomics
Rafael Irizarry

tSNE and UMAP plots:
"They really aren't informative, but they are really pretty."

Negative control scRNAseq data set: the percent of zeros is very high, and contributes strongly to the first PCA. tSNE plot 'discovers' new cells.

Transformed to log2(1 + CPM): looks zero-inflated.

Raw counts: Poisson

1/

Sophisticated swarming: #Bacteria support each other across generations
phys.org/news/2023-11-sophisti

Simultaneous spatiotemporal #transcriptomics and #microscopy of #Bacillus subtilis swarm development reveal cooperation across generations: Hannah Jeckel et al. nature.com/articles/s41564-023

"Living in communities provides many advantages to individual #microbes. They are more resilient against adverse environmental conditions, conquer new territories, and benefit from each other."

Yo #bioinformatics peeps, besides the #cmap dataset, are there are examples of good examples of Sample metadata organization?

I'm thinking specifically of ways to capture different experimental variables which can then be used for differential gene expression, but not only, in #Transcriptomics. E.g. fields are multiple treatments and concentrations, genotypes, siRNA Target, time point, etc.

I have a pretty good idea but I fear that I might be reinventing the wheel.

Hey there!
I'm a French researcher in developmental biology, focusing on mammalian sex determination and gonadal development at the genetic level. I have a PhD in bioinformatics but I do wet and dry lab.
I am a free (as in freedom) and open source software advocate, formerly actively involved in FOSS groups.
I love dataviz, photography, classic rock music, and playing video games.
I moved from another Mastodon instance.
#introductions #stem #DevBio #genetics #genomics #transcriptomics #SexDet

I forgot to do this, so here it is:
Hello #mastodon! I'm Luca, a #PhD student in #complexsystems at the University of Turin (#unito).

I mainly work in #genomics and #transcriptomics. My project involves the study of the #cancer #transportome, and its role in the overall #cellbiology.
I code in #python and #R, but i'm trying to (slowly) learn about #rustlang. I use #archlinux, btw.

I also play a ton of #boardgames and #videogames. I love #mechanicalkeyboard (s) and own a #corne myself.