ANOVA — anova • metabolyseR

One-way analysis of variance (ANOVA).

Usage

anova(
  x,
  cls = "class",
  pAdjust = "bonferroni",
  comparisons = list(),
  returnModels = FALSE
)

# S4 method for AnalysisData
anova(
  x,
  cls = "class",
  pAdjust = "bonferroni",
  comparisons = list(),
  returnModels = FALSE
)

Arguments

x: S4 object of class AnalysisData
cls: a vector of sample info column names to analyse
pAdjust: p value adjustment method
comparisons: list of comparisons to perform
returnModels: should models be returned

Examples

library(metaboData)

d <- analysisData(abr1$neg[,200:300],abr1$fact)

## Perform ANOVA
anova_analysis <- anova(d,cls = 'day')

## Extract significant features
explanatoryFeatures(anova_analysis)
#> # A tibble: 21 × 10
#>    response comparison  feature term        df  sumsq  meansq statistic  p.value
#>    <chr>    <chr>       <chr>   <chr>    <dbl>  <dbl>   <dbl>     <dbl>    <dbl>
#>  1 day      1~2~3~4~5~H N277    response     5 63072. 12614.       39.1 3.14e-23
#>  2 day      1~2~3~4~5~H N229    response     5 43549.  8710.       18.1 3.54e-13
#>  3 day      1~2~3~4~5~H N299    response     5  1211.   242.       16.4 3.87e-12
#>  4 day      1~2~3~4~5~H N295    response     5   271.    54.2      13.6 2.02e-10
#>  5 day      1~2~3~4~5~H N281    response     5   192.    38.5      12.5 1.16e- 9
#>  6 day      1~2~3~4~5~H N245    response     5  6268.  1254.       11.6 4.38e- 9
#>  7 day      1~2~3~4~5~H N255    response     5  5363.  1073.       11.0 1.14e- 8
#>  8 day      1~2~3~4~5~H N278    response     5   277.    55.4      10.9 1.48e- 8
#>  9 day      1~2~3~4~5~H N259    response     5  1236.   247.       10.8 1.72e- 8
#> 10 day      1~2~3~4~5~H N279    response     5   810.   162.       10.5 2.77e- 8
#> # ℹ 11 more rows
#> # ℹ 1 more variable: adjusted.p.value <dbl>