Single-cell analysis

Bioconductor branch, http://bioconductor.org/packages/release/BiocViews.html#___SingleCell.

benchmarks

Abdelaal et al. A comparison of automatic cell identification methods for single-cell RNA sequencing data. Genome Biol (2019) 20:194, https://doi.org/10.1186/s13059-019-1795-z

Single cell RNA-seq data analysis bundle.

Popescu D-M et al. Decoding human fetal liver haematopoiesis. Nature https://doi.org/10.1038/s41586-019-1652-y.

BayesPrism

GitHub: https://github.com/Danko-Lab/BayesPrism

Chu, T., Wang, Z., Pe’er, D. & Danko, C.G. Cell type and gene expression deconvolution with BayesPrism enables Bayesian integrative analysis across bulk and single-cell RNA sequencing in oncology. Nature Cancer 3, 505-517 (2022).

C2S-Scale

GitHub, https://github.com/vandijklab/cell2sentence (Hugging Face)

CReSCENT

Fullname: CanceR Single Cell ExpressioN Toolkit

Web: https://crescent.cloud/

Mohanraj, S., et al. (2020). "CReSCENT: CanceR Single Cell ExpressioN Toolkit." Nucleic Acids Research.

cytoSCAPE

GitHub: https://github.com/digitalcytometry/cytospace; Web: https://cytospace.stanford.edu/

DENDRO

Web: https://github.com/zhouzilu/DENDRO

Zhou Z, et al. DENDRO: genetic heterogeneity profiling and subclone detection by single-cell RNA sequencing. Genome Biol 21, 10 (2020). https://doi.org/10.1186/s13059-019-1922-x

SCANPY

Web: https://github.com/theislab/Scanpy

Updates: https://github.com/scverse/scanpy, https://scanpy.readthedocs.io/en/stable/

SCENIC

Web: https://aertslab.org/#scenic and https://pyscenic.readthedocs.io/en/latest/.

scGLUE

Web: https://scglue.readthedocs.io/en/latest/index.html

GitHub: https://github.com/gao-lab/GLUE

Cao ZJ, Gao G. Multi-omics single-cell data integration and regulatory inference with graph-linked embedding. Nat Biotechnol 40, 1458–1466 (2022). https://doi.org/10.1038/s41587-022-01284-4

scGPT

Web: https://github.com/bowang-lab/scGPT

Cui, H., Wang, C., Maan, H. et al. scGPT: toward building a foundation model for single-cell multi-omics using generative AI. Nat Methods 21, 1470–1480 (2024). https://doi.org/10.1038/s41592-024-02201-0

scMAGeCK

Web: https://bitbucket.org/weililab/scmageck/src/master/

Yang L, et al. scMAGeCK links genotypes with multiple phenotypes in single-cell CRISPR screens. Genome Biol 21, 19 (2020). https://doi.org/10.1186/s13059-020-1928-4

scvi-tools

Web: https://scvi-tools.org/

Seurat

Web: https://satijalab.org/seurat/

Stuart T, et al. Comprehensive Integration of Single-Cell Data. Cell. 2019;177(7):1888–1902.e21. doi:10.1016/j.cell.2019.05.031

Signac

Web: https://cloud.r-project.org/web/packages/Signac

Stuart, T., Srivastava, A., Madad, S., Lareau, C.A. & Satija, R. Single-cell chromatin state analysis with Signac. Nat Methods 18, 1333-1341 (2021).

souporcell

Web: https://github.com/wheaton5/souporcell

Heaton H, et al. Souporcell: robust clustering of single-cell RNA-seq data by genotype without reference genotypes. Nat Methods (2020). https://doi.org/10.1038/s41592-020-0820-1

squidpy

Web: https://squidpy.readthedocs.io/en/latest/.

Palla, G. et al. Squidpy: a scalable framework for spatial omics analysis. Nat Methods (2022).