ISOpureR: an R implementation of a computational purification algorithm of mixed tumour profiles
Author(s)Anghel, Catalina V.; Quon, Gerald; Haider, Syed; Nguyen, Francis; Deshwar, Amit G.; Morris, Quaid D.; Boutros, Paul C.; ... Show more Show less
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Background 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.
DepartmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Anghel, 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).
Final published version