Description Usage Arguments Details Value Author(s) Examples

This function allows to compute a post-hoc test after a 1-way
ANOVA analysis. It expects as input an object obtained with the function
`classic1wayAnova`

. The second parameter allows to choose between 2
different post-hoc tests: the Tukey Honest Significant Differences
(specified as "TukeyHSD") and the Dunnett test (specified as "Dunnett").

1 | ```
postHocTest(aov_fits, post_hoc_test = "TukeyHSD")
``` |

`aov_fits` |
a list containing aov fitted model objects |

`post_hoc_test` |
a character string indicating which post-hoc test to use. Possible values are "TukeyHSD" or "Dunnett". See details for what to choose according to your experimental design. |

This is a function allowing to realise post-hoc tests for a set of
proteins/peptides for which a classic 1-way anova has been performed with
the function `classic1wayAnova`

. Two types of tests are currently
available: The Tukey HSD's test and the Dunnett's test. Default is Tukey's
test.
The Tukey HSD's test compares all possible pairs of means, and is based on a
studentized range distribution. Here is used the `TukeyHSD()`

function,
which can be applied to balanced designs (same number of samples in each
group), but also to midly unbalanced designs.
The Dunnett's test compares a single control group to all other groups.
Make sure the factor levels are properly ordered.

a list of 2 dataframes: first one called "LogFC" contains all pairwise comparisons logFC values (one column for one comparison) for each analysed feature; The second one named "P_Value" contains the corresponding pvalues.

Hélène Borges

1 2 3 4 5 6 7 | ```
utils::data(Exp1_R25_prot, package='DAPARdata')
obj <- Exp1_R25_prot[1:1000]
keepThat <- mvFilterGetIndices(obj, condition='WholeMatrix', threshold=ncol(obj))
obj <- mvFilterFromIndices(obj, keepThat)
anova_tests <- t(apply(Biobase::exprs(obj),1, classic1wayAnova, conditions=as.factor(Biobase::pData(obj)$Condition)))
names(anova_tests) <- rownames(Biobase::exprs(obj))
pht <- postHocTest(aov_fits = anova_tests)
``` |

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