Discover and read the best of Twitter Threads about #BioC2020
Most recents (3)
Delighted to introduce correspondence analysis of scRNAseq. We show CA of Freeman-Tukey residuals outperforms CA of the Pearson Residuals
corral: Single-cell RNA-seq dimension reduction, batch integration, and visualization with correspondence analysis
biorxiv.org/content/10.110…
corral: Single-cell RNA-seq dimension reduction, batch integration, and visualization with correspondence analysis
biorxiv.org/content/10.110…
Code to reproduce figures are available at github.com/laurenhsu1/cor….
Functions are available in the corral @bioconductor package. bioconductor.org/packages/relea…
Functions are available in the corral @bioconductor package. bioconductor.org/packages/relea…
Decomposition of the Pearson Residuals is Correspondence analysis.
It's nicely described by displayr.com/math-correspon… .
I also described it in a workshop presented at #Bioc2020 and #Bioc2021 conferences aedin.github.io/PCAworkshop/ar…
Its fast and rapid to compute
It's nicely described by displayr.com/math-correspon… .
I also described it in a workshop presented at #Bioc2020 and #Bioc2021 conferences aedin.github.io/PCAworkshop/ar…
Its fast and rapid to compute
🔥off the press! 👀 our @biorxivpreprint on human 🧠brain @LieberInstitute spatial 🌌🔬transcriptomics data 🧬using Visium @10xGenomics🎉#spatialLIBD
🔍spatial.libd.org/spatialLIBD/
👩🏾💻github.com/LieberInstitut…
📚research.libd.org/spatialLIBD/
📦github.com/LieberInstitut…
biorxiv.org/content/10.110…
🔍spatial.libd.org/spatialLIBD/
👩🏾💻github.com/LieberInstitut…
📚research.libd.org/spatialLIBD/
📦github.com/LieberInstitut…
biorxiv.org/content/10.110…
Our study shows 12 samples from 3 human brain DLPFC neuronal layers + white matter with @10xGenomics's Visium platform. Features📜:
* Largest so far
* Harder to cluster than the example mouse data
* Data is all public
* @Bioconductor #rstats📦
* #shiny web app
2/7 #spatialLIBD
* Largest so far
* Harder to cluster than the example mouse data
* Data is all public
* @Bioconductor #rstats📦
* #shiny web app
2/7 #spatialLIBD
* Assessment of known markers
* Identification of layer-specific markers
* smFISH validation✅
* spatial registration of snRNA-seq data
* Layer-enrichment of neurodevelopmental and neuropsychiatric gene sets
* Data-driven layer-enriched clustering in the DLPFC
3/7 #spatialLIBD
* Identification of layer-specific markers
* smFISH validation✅
* spatial registration of snRNA-seq data
* Layer-enrichment of neurodevelopmental and neuropsychiatric gene sets
* Data-driven layer-enriched clustering in the DLPFC
3/7 #spatialLIBD
If you are interested in analyzing #SingleCell #RNAseq data in #Bioconductor using #rstats, please check out our paper Orchestrating single-cell analysis (OSCA) with @Bioconductor that was published in @naturemethods this week! #genomics #scRNAseq #dataviz #methodsmatter
@Bioconductor @naturemethods OSCA is a rich, reproducible, accessible (from beginners to experts!) resource with many #scRNAseq workflows & datasets. The resource is an online #bookdown book that compiles every night to track development by the open-source and open-development @Bioconductor #rstats community
@Bioconductor @naturemethods Now, OSCA is not the only set of packages / workflows for the analysis of #scRNAseq data. #Scanpy (scanpy.readthedocs.io/en/stable/) and #Seurat (satijalab.org/seurat/) and are two incredibly popular packages in #python and #rstats, respectively.
