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. 2023 May 4;39(5):btad329.
doi: 10.1093/bioinformatics/btad329.

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

Linda Grob  1   2 , Anne Bertolini  1   2 , Matteo Carrara  1   2 , Ulrike Lischetti  3 , Aizhan Tastanova  4 , Christian Beisel  5 , Mitchell P Levesque  4 , Daniel J Stekhoven  1   2 , Franziska Singer  1   2
Affiliations

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

Linda Grob et al. Bioinformatics. .

Abstract

Summary: 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 focused 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 and antibody expression 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.

Availability and implementation: gExcite 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).

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Figures

Figure 1.
Figure 1.
Overview of the workflow implemented in gExcite starting from raw fastq GEX and ADT files up until a combined analysis of GEX and ADT.
See this image and copyright information in PMC

References

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