Showing 4 open source projects for "method"

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    ggstatsplot

    ggstatsplot

    Enhancing {ggplot2} plots with statistical analysis

    ...In a typical exploratory data analysis workflow, data visualization and statistical modeling are two different phases: visualization informs modeling, and modeling in its turn can suggest a different visualization method, and so on and so forth. Bayesian hypothesis-testing. The central idea of {ggstatsplot} is simple: combine these two phases into one in the form of graphics with statistical details, which makes data exploration simpler and faster. Summary of statistical tests and effect sizes.
    Downloads: 0 This Week
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  • 2
    nichenetr

    nichenetr

    NicheNet: predict active ligand-target links between interacting cells

    nichenetr: the R implementation of the NicheNet method. The goal of NicheNet is to study intercellular communication from a computational perspective. NicheNet uses human or mouse gene expression data of interacting cells as input and combines this with a prior model that integrates existing knowledge on ligand-to-target signaling paths. This allows to predict ligand-receptor interactions that might drive gene expression changes in cells of interest.
    Downloads: 2 This Week
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  • 3

    MetEx

    MetEx is a computational tool for metabolite targered extraction and a

    ...So we developed a user-friendly and powerful software/webserver, MetEx, to both enable implementation of classical peak detection-based annotation and a new annotation method based on targeted extraction algorithms. The new annotation method based on targeted extraction algorithms can annotate more than 2 times metabolites than classical peak detection-based annotation method because it reduces the loss of metabolite signal in the data preprocessing process.
    Downloads: 0 This Week
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  • 4
    Statistics for Data Scientists

    Statistics for Data Scientists

    "Statistics for Data Scientists: 50 Essential Concepts"

    ...It aims to demystify the bridge between textbook statistics and empirical modeling by walking through assumption checking, visualization, interpreting outputs, and pitfalls of misuse. Throughout, the content emphasizes clarity and accessibility, showing not just how to run statistical tests or build models, but what they mean and when one method is preferred over another.
    Downloads: 0 This Week
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