Showing 5 open source projects for "cell"

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  • 1
    Seurat

    Seurat

    R toolkit for single cell genomics

    Seurat is a comprehensive R toolkit for single-cell genomics analysis, introduced by the Satija Lab at NYGC. It supports quality control, normalization, clustering, integration of multimodal data (e.g., scRNA‑seq, spatial, CITE‑seq), and visualization. Seurat v5 introduces scalable workflows and spatial transcriptomics support, commonly used in academic and industry research for single-cell studies.
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  • 2
    tidyr

    tidyr

    Tidy Messy Data

    tidyr is a core tidyverse package designed to help reshape and clean messy datasets into tidy data—i.e., data frames where each variable is a column, each observation is a row, and each value is a cell.
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  • 3
    nichenetr

    nichenetr

    NicheNet: predict active ligand-target links between interacting cells

    ...This model of prior information on potential ligand-target links can then be used to infer active ligand-target links between interacting cells. NicheNet prioritizes ligands according to their activity (i.e., how well they predict observed changes in gene expression in the receiver cell) and looks for affected targets with high potential to be regulated by these prioritized ligands.
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  • 4
    Harmony Data Integration

    Harmony Data Integration

    Fast, sensitive and accurate integration of single-cell data

    Harmony is a general-purpose R package with an efficient algorithm for integrating multiple data sets. It is especially useful for large single-cell datasets such as single-cell RNA-seq. Harmony has been tested on R versions =4. Please consult the DESCRIPTION file for more details on required R packages. Harmony has been tested on Linux, OS X, and Windows platforms.
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  • 5
    ComplexHeatmap

    ComplexHeatmap

    Make Complex Heatmaps

    ComplexHeatmap is an R/Bioconductor package by Zuguang Gu et al. designed to create highly flexible, complex, richly annotated heatmaps and related visualizations. It allows arranging multiple heatmaps, adding annotations, combining heatmaps, customizing colors, layouts, and integrating other plots. Often used in genomics/bioinformatics to show expression, methylation, etc., with sidebars, annotations, clustering, etc. Highly customizable layout: combining different heatmaps, arranging and...
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