JCVenterInstitute / NSForestLinks
A machine learning method for the discovery of the minimum marker gene combinations for cell type identification from single-cell RNA sequencing
☆66Updated 5 months ago
Alternatives and similar repositories for NSForest
Users that are interested in NSForest are comparing it to the libraries listed below
Sorting:
- Single-Cell Clustering Assessment Framework☆107Updated 2 years ago
- Inference of RNA velocity modules for prediction of cell fates and integration with spatial and regulatory models.☆85Updated 10 months ago
- Covarying neighborhood analysis (CNA) is a method for finding structure in- and conducting association analysis with multi-sample single-…☆56Updated 8 months ago
- Capybara: A computational tool to measure cell identity and fate transitions☆60Updated 3 years ago
- ☆48Updated 7 years ago
- Code to reproduce the analysis of "Decoding gene regulation in the mouse embryo using single-cell multi-omics""☆40Updated 3 years ago
- User-friendly tool to infer cell-cell interactions and communication from gene expression of interacting proteins☆69Updated 3 months ago
- Methods to compute Local Inverse Simpson's Index (LISI)☆73Updated 4 years ago
- Gene regulatory network containing signed transcription factor-target gene interactions☆98Updated 8 months ago
- Python implementation of Milo for differential abundance testing on KNN graph☆81Updated 11 months ago
- Context specific and dynamic gene regulatory network reconstruction and analysis☆127Updated 2 months ago
- Single Cell Cluster Evaluation☆99Updated 4 years ago
- Analysis of cell-cell communication at single-cell resolution☆106Updated last year
- ☆71Updated last year
- Python package for analysis of multiomic single cell RNA-seq and ATAC-seq.☆67Updated 7 months ago
- Snakemake pipeline that works with the scIB package to benchmark data integration methods.☆81Updated last year
- A method to rapidly assess cell type identity using both functional and random gene sets☆39Updated last year
- ☆53Updated 2 years ago
- pycisTopic is a Python module to simultaneously identify cell states and cis-regulatory topics from single cell epigenomics data.☆79Updated this week
- Finding surprising needles (=genes) in haystacks (=single cell transcriptome data).☆87Updated 2 months ago
- A tool that allows to get UMI counts from a single cell protein assay☆87Updated 9 months ago
- Clone of the Bioconductor repository for the scran package.☆46Updated last year
- Single-Cell Analysis of Inter-Individual Variability by Interpretable Tensor Decomposition☆63Updated last year
- A tool for unsupervised projection of single cell RNA-seq data☆96Updated 5 years ago
- Aligning gene expression trajectories of single-cell reference and query systems☆81Updated 6 months ago
- scAR (single-cell Ambient Remover) is a deep learning model for removal of the ambient signals in droplet-based single cell omics☆57Updated last year
- ☆53Updated 3 weeks ago
- ☆46Updated 3 years ago
- A repo with random short code snippets☆41Updated 6 years ago
- trajectory inference☆105Updated last year