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XenofilteR: computational deconvolution of mouse and human reads in tumor xenograft sequence data.

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cam.issuedOnline2018-10-04
dc.contributor.authorKluin, Roelof JC
dc.contributor.authorKemper, Kristel
dc.contributor.authorKuilman, Thomas
dc.contributor.authorde Ruiter, Julian R
dc.contributor.authorIyer, Vivek
dc.contributor.authorForment, Josep V
dc.contributor.authorCornelissen-Steijger, Paulien
dc.contributor.authorde Rink, Iris
dc.contributor.authorTer Brugge, Petra
dc.contributor.authorSong, Ji-Ying
dc.contributor.authorKlarenbeek, Sjoerd
dc.contributor.authorMcDermott, Ultan
dc.contributor.authorJonkers, Jos
dc.contributor.authorVelds, Arno
dc.contributor.authorAdams, David J
dc.contributor.authorPeeper, Daniel S
dc.contributor.authorKrijgsman, Oscar
dc.date.accessioned2018-10-05T06:02:43Z
dc.date.available2018-10-05T06:02:43Z
dc.date.issued2018-10-04
dc.date.updated2018-10-05T06:02:34Z
dc.description.abstractBACKGROUND: 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 .
dc.identifier.citationBMC Bioinformatics. 2018 Oct 04;19(1):366
dc.identifier.doi10.17863/CAM.30562
dc.identifier.eissn1471-2105
dc.identifier.issn1471-2105
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/283195
dc.language.isoeng
dc.language.rfc3066en
dc.publisherSpringer Science and Business Media LLC
dc.publisher.urlhttp://dx.doi.org/10.1186/s12859-018-2353-5
dc.rights.holderThe Author(s).
dc.subjectBreast cancer
dc.subjectCancer
dc.subjectMelanoma
dc.subjectNext-generation sequencing (NGS)
dc.subjectPatient-derived xenografts (PDX)
dc.subjectSequencing
dc.subjectXenograft
dc.subjectAnimals
dc.subjectComputers
dc.subjectDatabases, Genetic
dc.subjectHigh-Throughput Nucleotide Sequencing
dc.subjectHumans
dc.subjectMice
dc.titleXenofilteR: computational deconvolution of mouse and human reads in tumor xenograft sequence data.
dc.typeJournal Article
dcterms.dateAccepted2018-08-30
prism.publicationNameBMC Bioinformatics
rioxxterms.versionofrecord10.1186/s12859-018-2353-5

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