PomaOutliers {POMA} | R Documentation |
This function allows users to analyze outliers by different plots and remove them from an MSnSet object.
PomaOutliers( data, do = "clean", method = "euclidean", type = "median", coef = 1.5, labels = FALSE )
data |
A MSnSet object. First |
do |
Action to do. Options are "clean" (to remove detected outliers) and "analyze" (to analyze data outliers). Note that the output of this function will be different depending on this parameter. |
method |
Distance measure method to perform MDS. Options are "euclidean", "maximum", "manhattan", "canberra" and "minkowski". See |
type |
Type of outliers analysis to perform. Options are "median" (default) and "centroid". See |
coef |
This value corresponds to the classical 1.5 in Q3 + 1.5*IQR formula to detect outliers. By changing this value, the permissiveness in outlier detection will change. |
labels |
Logical indicating if sample IDs should to be plotted or not. |
A MSnSet object with cleaned data or different exploratory plots for the detailed analysis of outliers (depending on "do" parameter).
Pol Castellano-Escuder
data("st000336") # clean outliers st000336 %>% PomaImpute() %>% PomaNorm() %>% PomaOutliers() # analyze outliers st000336 %>% PomaImpute() %>% PomaNorm() %>% PomaOutliers(do = "analyze")