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@Arcadia-Science

Arcadia Science

Welcome to @Arcadia-Science!

At Arcadia, one of our central tenets is that our science should be maximally useful. Computational tasks are embedded in all aspects of our scientific inquiry, so we need our computing strategies to be maximally useful too. What does this mean? In addition to aligning with scientific priorities across Arcadia, we believe that useful computing is ✨ innovative, 👩‍💻usable, 🔁 reproducible.

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  1. ProteinCartography ProteinCartography Public

    A pipeline to build similarity maps of protein space

    Jupyter Notebook 45 13

  2. readlif readlif Public archive

    Leica Image Format (LIF) file reader for Python

    Python 39 14

  3. metagenomics metagenomics Public

    A Nextflow workflow for QC, evaluation, and profiling of metagenomic samples using short- and long-read technologies

    Nextflow 39 5

  4. glass-box-umap glass-box-umap Public

    Python package for making UMAP interpretable with exact feature contributions

    Python 33 1

  5. seqqc seqqc Public

    A Nextflow pipeline to identify quality control issues with new sequencing data.

    Groovy 30

  6. sourmashconsumr sourmashconsumr Public

    Working with the outputs of sourmash in R

    Standard ML 29 4

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