Citation¶

Citing PerturbScape¶

PerturbScape. Dey Lab, Memorial Sloan Kettering Cancer Center.
https://github.com/Deylab999MSKCC/perturbscape

Methods implemented¶

PerturbScape orchestrates published methods. If you use a specific module, please cite the method it implements alongside PerturbScape.

Contrastive PCA¶

Used by cpca and kcpca.

Abid, A., Zhang, M. J., Bagaria, V. K. & Zou, J. Exploring patterns enriched in a dataset with contrastive principal component analysis. Nature Communications 9, 2134 (2018).

Hotspot¶

Used by all seven embedding modules.

DeTomaso, D. & Yosef, N. Hotspot identifies informative gene modules across modalities of single-cell genomics. Cell Systems 12, 446–456 (2021).

Consensus NMF¶

Used by cnmf.

Kotliar, D. et al. Identifying gene expression programs of cell-type identity and cellular activity with single-cell RNA-Seq. eLife 8, e43803 (2019).

ContrastiveVI¶

Used by contrastivevi.

Weinberger, E., Lin, C. & Lee, S.-I. Isolating salient variations of interest in single-cell data with contrastiveVI. Nature Methods 20, 1336–1345 (2023).

DGCA¶

Used by de-dgca.

McKenzie, A. T., Katsyv, I., Song, W.-M., Wang, M. & Zhang, B. DGCA: A comprehensive R package for differential gene correlation analysis. BMC Systems Biology 10, 106 (2016).

Fastfood¶

Used by the kernel approximation in kcpca and kcontrapc.

Le, Q., Sarlós, T. & Smola, A. Fastfood — approximating kernel expansions in loglinear time. Proceedings of the 30th International Conference on Machine Learning (2013).

PoPS¶

The meta-program construction in stage 2 follows the Polygenic Priority Score approach.

Weeks, E. M. et al. Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases. Nature Genetics 55, 1267-1276 (2023).

sc-linker¶

The variant annotation and heritability enrichment steps follow the sc-linker framework.

Jagadeesh, K. A. et al. Identifying disease-critical cell types and cellular processes by integrating single-cell RNA-sequencing and human genetics. Nature Genetics 54, 1479-1492 (2022).

Stratified LD score regression¶

Finucane, H. K. et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nature Genetics 47, 1228-1235 (2015).

Gazal, S. et al. Linkage disequilibrium-dependent architecture of human complex traits shows action of negative selection. Nature Genetics 49, 1421-1427 (2017).

MAGMA¶

Gene-level association statistics used as the response in program selection and meta-program construction.

de Leeuw, C. A., Mooij, J. M., Heskes, T. & Posthuma, D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Computational Biology 11, e1004219 (2015).

ENCODE E2G¶

Variant-to-gene links used to convert meta-program genes into SNP annotations.

ENCODE Project Consortium. Expanded encyclopaedias of DNA elements in the human and mouse genomes. Nature 583, 699-710 (2020).

ConsensusPathDB¶

Pathway over-representation analysis of meta-program genes, drawing on its Reactome and WikiPathways collections.

Kamburov, A. & Herwig, R. ConsensusPathDB 2022: molecular interactions update as a resource for network biology. Nucleic Acids Research 50, D587-D595 (2022).

Core dependencies¶

Mölder, F. et al. Sustainable data analysis with Snakemake. F1000Research 10, 33 (2021).

Wolf, F. A., Angerer, P. & Theis, F. J. SCANPY: large-scale single-cell gene expression data analysis. Genome Biology 19, 15 (2018).

Data¶

Tables published through the Data Browser should be cited alongside the manuscript. If a Zenodo deposit is created for the full dataset, its DOI will be listed here.

Contact¶

Issues and questions: github.com/Deylab999MSKCC/perturbscape/issues