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bioRxiv · 10.1101/679183

XenoCell: classification of cellular barcodes in single cell experiments from xenograft samples

Cheloni, S.·Hillje, R.·Luzi, L.·Pelicci, P. G.·Gatti, E.
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Abstract

Single-cell sequencing technologies provide unprecedented opportunities to deconvolve the genomic, transcriptomic or epigenomic heterogeneity of complex biological systems. Its application in samples from xenografts of patient-derived biopsies (PDX), however, is limited by the presence in the analysed samples of a mixture of cells arising from the host and the graft.\n\nWe have developed XenoCell, the first stand-alone pre-processing tool that performs fast and reliable classification of host and graft cellular barcodes. We show its application on a single cell dataset composed by human and mouse cells.\n\nAvailability and implementationXenoCell is available for non-commercial use on GitLab: https://gitlab.com/XenoCell/XenoCell

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Cheloni, S., Hillje, R., Luzi, L., Pelicci, P. G., Gatti, E.. 2019-06-21. XenoCell: classification of cellular barcodes in single cell experiments from xenograft samples. https://doi.org/10.1101/679183

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