RT Journal Article
SR Electronic
T1 XenoCell: classification of cellular barcodes in single cell experiments from xenograft samples
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 679183
DO 10.1101/679183
A1 Stefano Cheloni
A1 Roman Hillje
A1 Lucilla Luzi
A1 Pier Giuseppe Pelicci
A1 Elena Gatti
YR 2019
UL http://biorxiv.org/content/early/2019/08/01/679183.abstract
AB 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.We 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.Availability and implementation XenoCell is available for non-commercial use on GitLab: https://gitlab.com/XenoCell/XenoCell