MiRNA-QC-and-Diagnosis: An R package for diagnosis based on MiRNA expression
Michele Castelluzzo,
Alessio Perinelli,
Simone Detassis,
Michela Alessandra Denti,
Leonardo Ricci
Affiliations
Michele Castelluzzo
Department of Physics, University of Trento, 38123 Trento, Italy
Alessio Perinelli
Department of Physics, University of Trento, 38123 Trento, Italy
Simone Detassis
Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, 38123 Trento, Italy
Michela Alessandra Denti
Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, 38123 Trento, Italy
Leonardo Ricci
Department of Physics, University of Trento, 38123 Trento, Italy; CIMeC, Center for Mind/Brain Sciences, University of Trento, 38068 Rovereto, Italy; Corresponding author at: Department of Physics, University of Trento, 38123 Trento, Italy.
The possibility of using microRNA (miRNA) levels as diagnostic and prognostic tools to detect different pathologies requires the implementation of reliable classifiers, whose training and use call for quality control of data corresponding to miRNA expression. In this work we present the MiRNA-QC-and-Diagnosis package. The package provides a set of functions for the R environment that implement the required quality control steps and thereupon allow to train, use and optimize a Bayesian classifier for diagnosis based on the measured miRNA expressions. The package thus makes up a complete and dedicated analytical toolbox for miRNA-based diagnosis.
