10.6084/m9.figshare.c.3595874_D5.v1
Elena Landoni
Elena
Landoni
Rosalba Miceli
Rosalba
Miceli
Maurizio Callari
Maurizio
Callari
Paola Tiberio
Paola
Tiberio
Valentina Appierto
Valentina
Appierto
Valentina Angeloni
Valentina
Angeloni
Luigi Mariani
Luigi
Mariani
Maria Daidone
Maria
Daidone
Additional file 1: of Proposal of supervised data analysis strategy of plasma miRNAs from hybridisation array data with an application to assess hemolysis-related deregulation
Springer Nature
2015
Data mining
Feature selection
Machine learning
Class prediction
High-dimensional data
SVM
Plasma miRNAs
2015-11-18 05:00:00
Dataset
https://springernature.figshare.com/articles/dataset/Additional_file_1_of_Proposal_of_supervised_data_analysis_strategy_of_plasma_miRNAs_from_hybridisation_array_data_with_an_application_to_assess_hemolysis-related_deregulation/4316882
R codes for implementing the described analyses (sample processing, data pre-processing, class comparison and class prediction). Caliper matching was implemented using the nonrandom package; the t- and the AD tests were implemented using the stats package and the adk package, respectively. Notice that the updated package for implementing the AD test is kSamples. As regards the bootstrap selection and the egg-shaped plot, we respectively modified the doBS and the importance igraph functions, both included in the bootfs package. For the SVM model we used the e1071 package. (R 12Â kb)