visualizeClusters: Visualize the clusters according to pvalue thresholds

Description Usage Arguments Value Author(s) Examples

View source: R/clustering.R

Description

Visualize the clusters according to pvalue thresholds

Usage

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visualizeClusters(
  dat,
  clust_model,
  adjusted_pValues,
  FDR_th = NULL,
  ttl = "",
  subttl = ""
)

Arguments

dat

the standardize data returned by the function [checkClusterability()]

clust_model

the clustering model obtained with dat.

adjusted_pValues

vector of the adjusted pvalues obtained for each protein with a 1-way ANOVA (for example obtained with the function [wrapperClassic1wayAnova()]).

FDR_th

the thresholds of FDR pvalues for the coloring of the profiles. The default (NULL) creates 4 thresholds: 0.001, 0.005, 0.01, 0.05 For the sake of readability, a maximum of 4 values can be specified.

ttl

title for the plot.

subttl

subtitle for the plot.

Value

a ggplot object

Author(s)

Helene Borges

Examples

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library(dplyr)
utils::data(Exp1_R25_prot, package='DAPARdata')
obj <- Exp1_R25_prot[1:100]
keepThat <- mvFilterGetIndices(obj, condition='WholeMatrix', threshold=ncol(obj))
obj <- mvFilterFromIndices(obj, keepThat)
expR25_ttest <- compute_t_tests(obj)
averaged_means <- averageIntensities(obj)
only_means <- dplyr::select_if(averaged_means, is.numeric)
only_features <- dplyr::select_if(averaged_means, is.character)
means <- purrr::map(purrr::array_branch(as.matrix(only_means), 1),mean)
centered <- only_means - unlist(means)
centered_means <- dplyr::bind_cols(feature = dplyr::as_tibble(only_features), dplyr::as_tibble(centered))
difference <- only_means[,1] - only_means[,2]
clusters <- as.data.frame(difference) %>%
    dplyr::mutate(cluster = dplyr::if_else(difference > 0, 1,2))
vizu <- visualizeClusters(dat = centered_means,
                          clust_model = as.factor(clusters$cluster),
                          adjusted_pValues = expR25_ttest$P_Value$`25fmol_vs_10fmol_pval`,
                          FDR_th = c(0.001,0.005,0.01,0.05),
                          ttl = "Clustering of protein profiles")
                          

DAPAR documentation built on April 11, 2021, 6 p.m.