XenoCell
The software tool 'XenoCell' addresses the challenge of distinguishing between host and graft sequence reads in single-cell sequencing experiments involving xenografts of patient-derived biopsies (PDX). This scenario involves the presence of cells from both the host and the graft, making it difficult to deconvolve their genomic information. 'XenoCell' is introduced as a standalone pre-processing tool capable of rapidly and reliably classifying cellular barcodes originating from the host and graft. The tool's efficacy is demonstrated through applications on mixed-species cell line experiments and a publicly available PDX dataset obtained via Drop-Seq. 'XenoCell' effectively disentangles sequence reads from a diverse range of host and graft species combinations, as well as various single-cell experiment platforms.
Topic
RNA-Seq;Gene expression
Detail
Operation: Sequencing quality control
Software interface: Command-line user inteface
Language: Python
License: The MIT licence
Cost: Free
Version name: -
Credit: Italian Ministry of Health, Fondazione Umberto Veronesi, European Research Council.
Input: -
Output: -
Contact: Pier Giuseppe Pelicci piergiuseppe.pelicci@ieo.it
Collection: -
Maturity: -
Publications
- XenoCell: classification of cellular barcodes in single cell experiments from xenograft samples
- Cheloni S, Hillje R, Luzi L, Pelicci PG, Gatti E. XenoCell: classification of cellular barcodes in single cell experiments from xenograft samples. BMC Med Genomics. 2021 Jan 29;14(1):34. doi: 10.1186/s12920-021-00872-8. PMID: 33514375; PMCID: PMC7847033.
- https://doi.org/10.1186/s12920-021-00872-8
- PMID: 33514375
- PMC: PMC7847033
Download and documentation
Documentation: https://gitlab.com/XenoCell/XenoCell/-/blob/master/README.md?ref_type=heads
Home page: https://gitlab.com/XenoCell/XenoCell
Links: https://gitlab.com/XenoCell/XenoCell/-/tree/master/examples?ref_type=heads
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