cna
importeddata/cna
Covarying neighborhood analysis (CNA) is a method for finding structure in- and conducting association analysis with multi-sample single-cell datasets.
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Data & Standards
- Subcategory
- unknown
- License
- GPL-3.0(osi)
- Status
- active
- Maturity
- deployed
- Organization
- immunogenomics
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/immunogenomics/cna
- Documentation
- unknown
- Tags
- python · single-cell
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- COVID-19-RNA-Seq-datasetssingle-cell
A repository for sharing information on available COVID-19 RNA-Seq datasets
- ligersingle-cell
R package for integrating and analyzing multiple single-cell datasets
- PISAsingle-cell
A collection of tools to process single-cell omics datasets.
- SCALEXsingle-cell
Online single-cell data integration through projecting heterogeneous datasets into a common cell-embedding space
- scAlignsingle-cell
A deep learning-based tool for alignment and integration of single cell genomic data across multiple datasets, species, conditions, batches
- scDatasetsingle-cell
scDataset: Scalable Data Loading for Deep Learning on Large-Scale Single-Cell Omics
- api.github.com/repos/immunogenomics/cnaretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2026-06-02, 57 stars, license reported as GPL-3.0. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/15.json→ .entries["cna"]
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