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#scrna_seq — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #scrna_seq, aggregated by home.social.

  1. Just published: UMAPs have become a very popular tool for visualizing high-dimensional data in biology, but they have significant drawbacks. In doi.org/10.1186/s12859-024-059 Kitanovski et al describe scBubbletree (sc because our focus is on single cell data) as a better alternative: it is easier to interpret, quantitative, and allows for integration of different types of data. The method is implemented in a free, open source R package (bioconductor.org/packages/rele). I am sure that this type of quantitative visualization is beneficial beyond single cell gene expression data.

    #umap #scRNA_seq #bioinformatics

  2. Just published: UMAPs have become a very popular tool for visualizing high-dimensional data in biology, but they have significant drawbacks. In doi.org/10.1186/s12859-024-059 Kitanovski et al describe scBubbletree (sc because our focus is on single cell data) as a better alternative: it is easier to interpret, quantitative, and allows for integration of different types of data. The method is implemented in a free, open source R package (bioconductor.org/packages/rele). I am sure that this type of quantitative visualization is beneficial beyond single cell gene expression data.

    #umap #scRNA_seq #bioinformatics

  3. Need to integrate #SingleCellOmics datasets? This new paper by SIB's @Carmona et al.
    introduces STACAS, a flexible framework to reduce batch effect in #scrna_seq data by taking advantage of prior cell type knowledge nature.com/articles/s41467-024

  4. Need to integrate #SingleCellOmics datasets? This new paper by SIB's @Carmona et al.
    introduces STACAS, a flexible framework to reduce batch effect in #scrna_seq data by taking advantage of prior cell type knowledge nature.com/articles/s41467-024

  5. Need to integrate #SingleCellOmics datasets? This new paper by SIB's @Carmona et al.
    introduces STACAS, a flexible framework to reduce batch effect in #scrna_seq data by taking advantage of prior cell type knowledge nature.com/articles/s41467-024

  6. Need to integrate #SingleCellOmics datasets? This new paper by SIB's @Carmona et al.
    introduces STACAS, a flexible framework to reduce batch effect in #scrna_seq data by taking advantage of prior cell type knowledge nature.com/articles/s41467-024

  7. Need to integrate #SingleCellOmics datasets? This new paper by SIB's @Carmona et al.
    introduces STACAS, a flexible framework to reduce batch effect in #scrna_seq data by taking advantage of prior cell type knowledge nature.com/articles/s41467-024