gExcite – a start-to-end framework for single-cell gene expression, hashing, and antibody analysis

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Recently, CITE-seq emerged as a multimodal single-cell technology capturing gene expression and surface protein information from the same single-cells, which allows unprecedented insights into disease mechanisms and heterogeneity, as well as immune cell profiling. Multiple single-cell profiling methods exist, but they are typically focussed on either gene expression or antibody analysis, not their combination. Moreover, existing software suites are not easily scalable to a multitude of samples. To this end, ETH Zurich researchers designed gExcite, a start-to-end workflow that provides both gene and antibody expression analysis, as well as hashing deconvolution. Embedded in the Snakemake workflow manager, gExcite facilitates reproducible and scalable analyses. The researchers showcase the output of gExcite on a study of different dissociation protocols on PBMC samples.

gExcite pipeline

rna-seq

Availability: gExcite is open source available on github at https://github.com/ETH-NEXUS/gExcite_pipeline.


Grob L, Bertolini A, Carrara M, Lischetti U, Tastanova A, Beisel C, Levesque MP, Stekhoven DJ, Singer F. (2023) gExcite – A start-to-end framework for single-cell gene expression, hashing, and antibody analysis. Bioinformatics [Epub ahead of print]. [abstract]
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