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dc.contributor.authorAnghel, Catalina V.
dc.contributor.authorQuon, Gerald
dc.contributor.authorHaider, Syed
dc.contributor.authorNguyen, Francis
dc.contributor.authorDeshwar, Amit G.
dc.contributor.authorMorris, Quaid D.
dc.contributor.authorBoutros, Paul C.
dc.date.accessioned2015-06-29T17:01:29Z
dc.date.available2015-06-29T17:01:29Z
dc.date.issued2015-05
dc.date.submitted2014-11
dc.identifier.issn1471-2105
dc.identifier.urihttp://hdl.handle.net/1721.1/97560
dc.description.abstractBackground Tumour samples containing distinct sub-populations of cancer and normal cells present challenges in the development of reproducible biomarkers, as these biomarkers are based on bulk signals from mixed tumour profiles. ISOpure is the only mRNA computational purification method to date that does not require a paired tumour-normal sample, provides a personalized cancer profile for each patient, and has been tested on clinical data. Replacing mixed tumour profiles with ISOpure-preprocessed cancer profiles led to better prognostic gene signatures for lung and prostate cancer. Results To simplify the integration of ISOpure into standard R-based bioinformatics analysis pipelines, the algorithm has been implemented as an R package. The ISOpureR package performs analogously to the original code in estimating the fraction of cancer cells and the patient cancer mRNA abundance profile from tumour samples in four cancer datasets. Conclusions The ISOpureR package estimates the fraction of cancer cells and personalized patient cancer mRNA abundance profile from a mixed tumour profile. This open-source R implementation enables integration into existing computational pipelines, as well as easy testing, modification and extension of the model.en_US
dc.description.sponsorshipProstate Cancer Canadaen_US
dc.description.sponsorshipMovember Foundation (Grant RS2014-01)en_US
dc.publisherBioMed Centralen_US
dc.relation.isversionofhttp://dx.doi.org/10.1186/s12859-015-0597-xen_US
dc.titleISOpureR: an R implementation of a computational purification algorithm of mixed tumour profilesen_US
dc.typeArticleen_US
dc.identifier.citationAnghel, Catalina V, Gerald Quon, Syed Haider, Francis Nguyen, Amit G Deshwar, Quaid D Morris, and Paul C Boutros. “ISOpureR: An R Implementation of a Computational Purification Algorithm of Mixed Tumour Profiles.” BMC Bioinformatics 16, no. 1 (May 14, 2015).en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.mitauthorQuon, Geralden_US
dc.relation.journalBMC Bioinformaticsen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2015-06-29T08:39:43Z
dc.language.rfc3066en
dc.rights.holderAnghel et al.; licensee BioMed Central.
dspace.orderedauthorsAnghel, Catalina V; Quon, Gerald; Haider, Syed; Nguyen, Francis; Deshwar, Amit G; Morris, Quaid D; Boutros, Paul Cen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-1716-0153
mit.licenseOPEN_ACCESS_POLICYen_US


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