Showing 5 open source projects for "python package"

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  • 1
    harmonypy

    harmonypy

    Integrate multiple high-dimensional datasets with fuzzy k-means

    Harmony is an algorithm for integrating multiple high-dimensional datasets. harmonypy is a port of the harmony R package by Ilya Korsunsky. 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.
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  • 2
    reticulate

    reticulate

    R Interface to Python

    reticulate is an R package from Posit that creates seamless interoperability between R and Python. It lets you call Python modules, classes, and functions from within R, automatically translating between R and Python data structures. Useful for combining Python tooling with R projects, data analysis, and RMarkdown reports.
    Downloads: 0 This Week
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  • 3
    Mara Pipelines

    Mara Pipelines

    A lightweight opinionated ETL framework, halfway between plain scripts

    This package contains a lightweight data transformation framework with a focus on transparency and complexity reduction. Data integration pipelines as code: pipelines, tasks and commands are created using declarative Python code. PostgreSQL as a data processing engine. Extensive web ui. The web browser as the main tool for inspecting, running and debugging pipelines.
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  • 4
    scArches

    scArches

    Reference mapping for single-cell genomics

    Single-cell architecture surgery (scArches) is a package for reference-based analysis of single-cell data. scArches allows your single-cell query data to be analyzed by integrating it into a reference atlas. By mapping your data into an integrated reference you can transfer cell-type annotation from reference to query, identify disease states by mapping to healthy atlas, and advanced applications such as imputing missing data modalities or spatial locations.
    Downloads: 0 This Week
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  • 5
    Hetionet

    Hetionet

    Hetionet: an integrative network of disease

    ...The JSON and Neo4j formats contain node and edge properties, which are absent in the TSV and matrix formats, including licensing information. Therefore the recommended formats are JSON and Neo4j. Our hetio package in Python reads the JSON format, but it is otherwise a simple yet new format. The Neo4j graph database has an established and thriving ecosystem. However, if you would like to access Hetionet without Neo4j, then we suggest the JSON format. The matrix format refers to HetMat archives, which store edge adjacency matrices on disk. ...
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