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bioRxiv · 10.1101/2022.05.23.490488

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

Grob, L.·Bertolini, A.·Carrara, M.·Menzel, U.·Tastanova, A.·Beisel, C.·Levesque, M. P.·Stekhoven, D. J.·Singer, F.
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Abstract

SummarySingle-cell RNA sequencing (scRNA-seq) based gene expression analysis is now an established powerful technique to decipher tissues at a single-cell level. 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, we designed gExcite, a start-to-end workflow that provides both gene expression and CITE-seq analysis, as well as hashing deconvolution. Embedded in the Snakemake workflow manager, gExcite facilitates reproducible and scalable analyses. We showcase the output of gExcite on a study of different dissociation protocols on PBMC samples. AvailabilitygExcite is open source available on github at https://github.com/ETH-NEXUS/gExcite_pipeline The software is distributed under the GNU General Public License 3 (GPL3). Contactsinger@nexus.ethz.ch Supplementary InformationSupplementary information is available at the journals web site.

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Grob, L., Bertolini, A., Carrara, M., Menzel, U., Tastanova, A., Beisel, C., Levesque, M. P., Stekhoven, D. J., Singer, F.. 2022-05-24. gExcite - A start-to-end framework for single-cell gene expression, hashing, and antibody analysis. https://doi.org/10.1101/2022.05.23.490488

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