BACKGROUND: Mouse xenografts from (patient-derived) tumors (PDX) or tumor cell 
lines are widely used as models to study various biological and preclinical 
aspects of cancer. However, analyses of their RNA and DNA profiles are 
challenging, because they comprise reads not only from the grafted human cancer 
but also from the murine host. The reads of murine origin result in false 
positives in mutation analysis of DNA samples and obscure gene expression levels 
when sequencing RNA. However, currently available algorithms are limited and 
improvements in accuracy and ease of use are necessary.
RESULTS: We developed the R-package XenofilteR, which separates mouse from human 
sequence reads based on the edit-distance between a sequence read and reference 
genome. To assess the accuracy of XenofilteR, we generated sequence data by in 
silico mixing of mouse and human DNA sequence data. These analyses revealed that 
XenofilteR removes > 99.9% of sequence reads of mouse origin while retaining 
human sequences. This allowed for mutation analysis of xenograft samples with 
accurate variant allele frequencies, and retrieved all non-synonymous somatic 
tumor mutations.
CONCLUSIONS: XenofilteR accurately dissects RNA and DNA sequences from mouse and 
human origin, thereby outperforming currently available tools. XenofilteR is 
open source and available at https://github.com/PeeperLab/XenofilteR .