#scrnaseq — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #scrnaseq, aggregated by home.social.
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The main #ECCB2026 conference may be over, but today lots of great people are meeting to discuss single-cell standards and collaborations:
Single-cell and spatial data FAIRification, community standards and training
organised by @fbastian @SIB & @elixir_europe
eccb2026.org/communities-day#single-cell-and-spatial-data-fairification
#scRNAseq #SingleCell #FAIRdata #bioinformatics #OpenData #GenevaLovesData -
Pipeline release! nf-core/scnanoseq v1.3.0 - nf-core/scnanoseq v1.3.0 - Steel Elephant!
Single-cell/nuclei pipeline for data derived from Oxford Nanopore and 10X Genomics
Please see the changelog: https://github.com/nf-core/scnanoseq/releases/tag/1.3.0#10xgenomics #longreadsequencing #nanopore #rnaseq #rnaseq #scrnaseq #singlecell #nfcore #openscience #nextflow #bioinformatics
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Aligning #scRNAseq datasets along a shared temporal axis across studies, species & systems is hard. This study uses meta-analytic models to develop a #transcriptomic measure of #neurodevelopmental timing that is applicable to different organisms & tissue types @PLOSBiology https://plos.io/4ch0XiX
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Pipeline release! nf-core/scnanoseq v1.2.2 - nf-core/scnanoseq v1.2.2 - Thallium Tiger!
Please see the changelog: https://github.com/nf-core/scnanoseq/releases/tag/1.2.2
#10xgenomics #longreadsequencing #nanopore #rnaseq #scrnaseq #singlecell #nfcore #openscience #nextflow #bioinformatics
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Surprised to see @Bioconductor methods missing from this #bioinformatics preprint comparing #Seurat and #scanpy for #scRNAseq. Not even a mention that Bioconductor is popular to analyze single cell data. Sometimes it is amazing what a company (10x genomics) recommending a OSS software can do to a community: https://www.biorxiv.org/content/10.1101/2024.04.04.588111v1
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Hello #scrnaseq wizards out there! Anyone can help answer this question?
https://www.biostars.org/p/9578398/I'm happy with the #Seurat + #Signac pipeline but I'm not sure what to do and how to merge the two sets of data (#multiomics and #scRNAseq)
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Last talk of the #CSSingleCells23 conference:
Karin Pelka, Gladstone/UCSF
https://pelkalab.org/Spatially organized #immune hubs in #colon #cancer
#ColonCancer
#scRNAseqhttps://pubmed.ncbi.nlm.nih.gov/34450029/
Then: predict cellular interaction networks via correlations of gene program activities across #tumors
anti-tumor hubs in tumors, ISGs including CXCR3 ligands, differs between tumor types (MMR+ or -)
have data from clinical trial (biopsies before and after treatment)
https://pubmed.ncbi.nlm.nih.gov/36702949/1/2
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First speaker of the session (Cell identity in situ)
is Elana Fertig
of Convergence Institute at Johns Hopkins
https://fertiglab.com/She has background in weather prediction (!) ⛈️ which has convergence with predictive medicine (such as huge data sets)
Looks at #PancreaticCancer with spatial #proteomics
now #scRNAseqDeveloped CoGAPS matrix factorization, can identify cell state transitions
Using PhysiCell to build models
http://physicell.org/#cancer
#SingleCell
#CSSingleCells231/2
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"predicts new biology missed by today's genomics"
#spatial #transcriptomics #genomics
#scrnaseq
#CSSingleCells23works by unified detection of sample-specific sequence variation... sample can be different cells, sequence is raw reads
method chooses an "anchor" sequence then looks for neighboring sequence that varies. thus is independent of any reference genome
https://www.biorxiv.org/content/10.1101/2022.06.24.497555v4
https://www.biorxiv.org/content/10.1101/2023.03.17.533189v2New insights into universally expressed human genes
https://www.biorxiv.org/content/10.1101/2022.12.06.519414v12/3
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" Instead, #Hepatoblastoma #tumors contain a large suppressive #myeloid compartment which poses opportunities for targeting. Specifically, therapeutic antibodies
targeting the #tumor antigen #GPC3 to induce ADCP by #macrophages, in combination with myeloid
#ImmuneCheckpointBlockade (#CD47/SIRPa, or VISTA) could be a feasible strategy to explore in future studies"Krijgsman et al. from Vercoulen lab in the #UMCUtrecht, on #bioRXiv:
https://www.biorxiv.org/content/10.1101/2023.06.28.546852v1