PomaUnivariate {POMA} | R Documentation |
PomaUnivariate() allows users to perform different univariate statistical analysis on MS data.
PomaUnivariate( data, covariates = FALSE, method = "ttest", paired = FALSE, var_equal = FALSE, adjust = "fdr" )
data |
A MSnSet object. First |
covariates |
Logical. If it's set to |
method |
Univariate statistical method. Options are: "ttest", "anova", "mann" and "kruskal". |
paired |
Logical that indicates if the data is paired or not. |
var_equal |
Logical that indicates if the data variance is equal or not. |
adjust |
Multiple comparisons correction method. Options are: "fdr", "holm", "hochberg", "hommel", "bonferroni", "BH" and "BY". |
A data frame with results.
Pol Castellano-Escuder
data("st000336") data("st000284") # ttest st000336 %>% PomaImpute() %>% PomaNorm() %>% PomaOutliers() %>% PomaUnivariate(method = "ttest") # ANOVA st000284 %>% PomaImpute() %>% PomaNorm() %>% PomaOutliers() %>% PomaUnivariate(method = "anova")