# Shiny-based interactive data-quality exploration for omics data

## Documentation for package ‘MatrixQCvis’ version 1.2.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

barplot_samples_memi | Barplot of number of measured/missing features of samples
batchCorrectionAssay | Remove batch effects from (count/intensity) values of a 'SummarizedExperiment'
biocrates | Convert Biocrates xlsx output to 'SummarizedExperiment' object
createDfFeature | Create data frame of (count/intensity) values for a selected feature along data processing steps
create_boxplot | Create a boxplot of (count/intensity) values per sample
cv | Calculate coefficient of variation
cvFeaturePlot | Plot of feature-wise coefficient of variation values
distSample | Create a heatmap using distance information between samples
distShiny | Create distance matrix from numerical matrix
driftPlot | Plot the trend line for aggregated values
ECDF | Create ECDF plot of a sample against a reference
explVar | Retrieve the explained variance for each principal component (PCA) or axis (PCoA)
extractComb | Obtain the features that are present in a specified set
featurePlot | Create a plot of (count/intensity) values over the samples
hist_feature | Histogram for measured value per feature
hist_feature_category | Histogram of features per sample type
hist_sample | Plot a histogram of the number of a category
hist_sample_num | Return the number of a category
hoeffDPlot | Create a plot from a list of Hoeffding's D values
hoeffDValues | Create values of Hoeffding's D statistics from M and A values
imputeAssay | Impute missing values in a 'matrix'
MAplot | Create a MA plot
MAvalues | Create values (M and A) for MA plot
maxQuant | Convert MaxQuant xlsx output to 'SummarizedExperiment' object
measured_category | Obtain the number of measured intensities per sample type
mosaic | Mosaic plot for two factors in colData(se)
normalizeAssay | Normalize a data sets (reduce technical sample effects)
ordination | Dimensionality reduction with ordination methods PCA, PCoA, NMDS, UMAP and tSNE
ordinationPlot | Plot the coordinates from 'ordination' values
permuteExplVar | Permute the expression values and retrieve the explained variance
plotCV | Plot CV values
plotPCALoadings | Plot for PCA loadings of features
plotPCAVar | Plot of explained variance against the principal components
plotPCAVarPvalue | Plot p-values for the significance of principal components
samples_memi | Create tibble containing number of measured/missing features of samples
shinyQC | Shiny application for initial QC exploration of -omics data sets
sumDistSample | Plot the sum of distances to other samples
tblPCALoadings | Return tibble with PCA loadings for features
transformAssay | Transform the (count/intensity) values of a 'data.frame', 'tbl' or 'matrix'
upset_category | UpSet plot to display measures values across sample types
volcanoPlot | Volcano plot of fold changes/differences against p-values