PomaUnivariate: Univariate Statistical Methods for Mass Spectrometry Data

Description Usage Arguments Value Author(s) Examples

View source: R/PomaUnivariate.R

Description

PomaUnivariate() allows users to perform different univariate statistical analysis on MS data.

Usage

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PomaUnivariate(
  data,
  covariates = FALSE,
  method = "ttest",
  paired = FALSE,
  var_equal = FALSE,
  adjust = "fdr"
)

Arguments

data

A MSnSet object. First pData column must be the subject group/type.

covariates

Logical. If it's set to TRUE all metadata variables stored in pData will be used as covariables. Default = FALSE.

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".

Value

A data frame with results.

Author(s)

Pol Castellano-Escuder

Examples

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data("st000336")
data("st000284")

# ttest
st000336 %>% 
  PomaImpute() %>%
  PomaNorm() %>%
  PomaOutliers() %>%
  PomaUnivariate(method = "ttest")

# ANOVA
st000284 %>% 
  PomaImpute() %>%
  PomaNorm() %>%
  PomaOutliers() %>%
  PomaUnivariate(method = "anova")

pcastellanoescuder/POMA documentation built on May 14, 2021, 11:07 p.m.