GitHub / parashardhapola / scarf

Toolkit for highly memory efficient analysis of single-cell RNA-Seq, scATAC-Seq and CITE-Seq data. Analyze atlas scale datasets with millions of cells on laptop.

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Commits: 896
Authors: 5
Mean commits per author: 179.2
Development Distribution Score: 0.177
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Topics: big-data, bioinformatics, cite-seq, clustering, differential-expression, dimension-reduction, gene-modules, genomics, graph-analytics, memory-efficient, multiomics, pseudotime, scalable-data-analysis, scatac-seq, scrna-seq, single-cell-atac-seq, single-cell-genomics, single-cell-rna-seq, tsne, umap

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