MicroCellClust: mining rare and highly specific subpopulations from single-cell expression data

This repository contains the breast cancer scRNA-seq data used in sections 3.1, 3.3 and 3.4 of the MicroCellClust paper, published in Bioinformatics [1]. The other datasets, used in sections 3.2 and 3.5, are also publicly available (Sequence Read Archive, SRX1723923, and Gene Expression Omnibus, GSE65525).

This repository also contains the version (v1.2) of the MicroCellClust solver implementation used to produce the results described in the paper. The latest version of the software is available at https://github.com/agerniers/MicroCellClust

Version 2 of MicroCellClust [2], suitable for large-scale single-cell data, is available at https://github.com/agerniers/MicroCellClust

References

[1] A. Gerniers, O. Bricard and P. Dupont (2021). MicroCellClust: mining rare and highly specific subpopulations from single-cell expression data. Bioinformatics, 37(19), 3220-3227. https://doi.org/10.1093/bioinformatics/btab239

[2] A. Gerniers, P. Dupont (2022). MicroCellClust 2: a hybrid approach for multivariate rare cell mining in large-scale single-cell data. In 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 148-153.