Identifying Extreme Observations, Outliers and Noise in Clinical and Genetic Data
C. Arenas, Claudio Toma, Bru Cormand, Itziar Irigoien · Current Bioinformatics · 2016
Background: Currently, a major challenge is the treatment and interpretation of actual data. Data sets are often high-dimensional, have small number of observations and are noisy. Furthermore, in recent years, many approaches have been suggested for integrating continuous with categorical/ordinal data, in order to capture the information which is lost in independent studies. Keywords: Biomedical data, data depth, gene expression, microarray, noise, outlier, robust estimation.