Package 'omXplore'

Title:	Vizualization tools for 'omics' datasets with R
Description:	This package contains a collection of functions (written as shiny modules) for the visualisation and the statistical analysis of omics data. These plots can be displayed individually or embedded in a global Shiny module. Additionaly, it is possible to integrate third party modules to the main interface of the package omXplore.
Authors:	Samuel Wieczorek [aut, cre] , Thomas Burger [aut], Enora Fremy [ctb]
Maintainer:	Samuel Wieczorek <[email protected]>
License:	Artistic-2.0
Version:	1.1.0
Built:	2024-12-03 06:01:19 UTC
Source:	https://github.com/bioc/omXplore

Help Index

Accessors functions
Builds enriched assay with cell metadata info
Build color style for DT tables
Color legend for DaparToolshed
Convert to enriched MultiAssayExperiment
Displays a correlation matrix of the quantitative data of a numeric matrix.
Customised resetZoom Button of highcharts plots
#' @title Customised contextual menu of highcharts plots
Displays a correlation matrix of the quantitative data of a numeric matrix.
Bar plot of missing values per lines using highcharter.
Bar plot of missing values per lines using highcharter.
External module example
formatDT_ui and formatDT_server
Constructs a dataset suitable to use with the module format_DT.
Package version
Global variables
Displays different intensity plots.
Checks the class of a list's slots
Displays a correlation matrix of the quantitative data of a numeric matrix.
Explore MultiAssayExperiment objects.
Shiny modules used by omXplore
Palette for samples.
Display a CC
Loads packages
Variance plot
Convert datasets exported by the package Prostar
Quantitative metadata vocabulary for entities
Feature example data
Feature example data

Accessors functions

Description

Functions used to access the additional plots in the instances of the class MultiAssayExperiment.

Usage

get_adjacencyMatrix(object, ...)

## S4 method for signature 'SummarizedExperiment'
get_adjacencyMatrix(object)

get_group(object, ...)

## S4 method for signature 'MultiAssayExperiment'
get_group(object)

get_metacell(object, ...)

## S4 method for signature 'SummarizedExperiment'
get_metacell(object, slot.name = c("metacell", "qMetacell"))

get_cc(object, ...)

## S4 method for signature 'SummarizedExperiment'
get_cc(object)

get_parentProtId(object, ...)

## S4 method for signature 'SummarizedExperiment'
get_parentProtId(object)

get_colID(object, ...)

## S4 method for signature 'SummarizedExperiment'
get_colID(object)

get_type(object, ...)

## S4 method for signature 'SummarizedExperiment'
get_type(object)

get_pkg_version(object, ...)

## S4 method for signature 'SummarizedExperiment'
get_pkg_version(object)
get_adjacencyMatrix(object, ...)

## S4 method for signature 'SummarizedExperiment'
get_adjacencyMatrix(object)

get_group(object, ...)

## S4 method for signature 'MultiAssayExperiment'
get_group(object)

get_metacell(object, ...)

## S4 method for signature 'SummarizedExperiment'
get_metacell(object, slot.name = c("metacell", "qMetacell"))

get_cc(object, ...)

## S4 method for signature 'SummarizedExperiment'
get_cc(object)

get_parentProtId(object, ...)

## S4 method for signature 'SummarizedExperiment'
get_parentProtId(object)

get_colID(object, ...)

## S4 method for signature 'SummarizedExperiment'
get_colID(object)

get_type(object, ...)

## S4 method for signature 'SummarizedExperiment'
get_type(object)

get_pkg_version(object, ...)

## S4 method for signature 'SummarizedExperiment'
get_pkg_version(object)

Arguments

`object`	An instance of class `SummarizedExperiment`.
`...`	Additional parameters
`slot.name`	The name of the slot dedicated to cell metadata to search. Default values are 'metacell' and 'qMetacell'

Value

See individual method description for the return value.

If exists, the slot value requested.

A DataFrame containing the adjacency matrix of the dataset

A data.frame containing the metadata of the dataset

Examples


## -----------------------------------
## Accessing slots from a MSnSet dataset
## -----------------------------------
data(sub_R25)
se1 <- sub_R25[[1]]
parentProtId <- get_parentProtId(se1)
colID <- get_colID(se1)
type <- get_type(se1)
metacell <- get_metacell(se1)
conds <- get_group(sub_R25)

## -----------------------------------
## Accessing slots from a MSnSet dataset
## -----------------------------------
data(sub_R25)
se1 <- sub_R25[[1]]
parentProtId <- get_parentProtId(se1)
colID <- get_colID(se1)
type <- get_type(se1)
metacell <- get_metacell(se1)
conds <- get_group(sub_R25)

Builds enriched assay with cell metadata info

Description

If the cell metadata exists in the object of class SummarizedExperiment, then these information are added to the quantitative data so as to use styles with the functions of the package DT.

Usage

Build_enriched_qdata(obj)
Build_enriched_qdata(obj)

Arguments

obj

An instance of the class SummarizedExperiment

Value

A data.frame with new colums corresponding to the cell metadata (if exists)

Build color style for DT tables

Description

This function builds a list which is used for styling DT tables with the function DT::styleEqual()

Usage

BuildColorStyles(type)
BuildColorStyles(type)

Arguments

type

The type of dataset. Available values are protein and peptide

Value

A list

Color legend for DaparToolshed

Description

Shows a legend based on the tags in the package 'DaparToolshed'

Usage

custom_metacell_colors()

colorLegend_ui(id)

colorLegend_server(
  id,
  presentTags = reactive({
     NULL
 }),
  hide.white = TRUE
)

colorLegend(obj = SummarizedExperiment::SummarizedExperiment())
custom_metacell_colors()

colorLegend_ui(id)

colorLegend_server(
  id,
  presentTags = reactive({
     NULL
 }),
  hide.white = TRUE
)

colorLegend(obj = SummarizedExperiment::SummarizedExperiment())

Arguments

`id`	A `character(1)` which is the id of the shiny module.
`presentTags`	A vector of `character()` which correspond to the tags.
`hide.white`	A `boolean()` to indicate whether the white cells must be hidden or not.
`obj`	An instance of the class `SummarizedExperiment`.

Value

A vector

A shiny app

Examples


data(vdata)
shiny::runApp(colorLegend(vdata[[1]]))


data(vdata)
shiny::runApp(colorLegend(vdata[[1]]))

Convert to enriched MultiAssayExperiment

Description

The resulting object is an instance of the MultiAssayExperiment class. F

Usage

convert_to_mae(obj)

MSnSet_to_mae(obj)

matrix_to_mae(obj)

df_to_mae(obj)

Compute_CC(obj)

QFeatures_to_mae(obj)

SE_to_mae(obj)

MAE_to_mae(obj)

Check_se_Consistency(obj)

list_to_se(ll)

Check_List_consistency(ll)

listOfLists_to_mae(obj, colData = NULL)

listOfSE_to_mae(obj)

Check_MSnSet_Consistency(obj)

matrix_to_se(obj)

df_to_se(obj)

MSnSet_to_se(obj)

Build_X_CC(se)

listOfMSnSet_to_mae(obj)

listOfmatrix_to_mae(obj)

listOfdf_to_mae(obj)
convert_to_mae(obj)

MSnSet_to_mae(obj)

matrix_to_mae(obj)

df_to_mae(obj)

Compute_CC(obj)

QFeatures_to_mae(obj)

SE_to_mae(obj)

MAE_to_mae(obj)

Check_se_Consistency(obj)

list_to_se(ll)

Check_List_consistency(ll)

listOfLists_to_mae(obj, colData = NULL)

listOfSE_to_mae(obj)

Check_MSnSet_Consistency(obj)

matrix_to_se(obj)

df_to_se(obj)

MSnSet_to_se(obj)

Build_X_CC(se)

listOfMSnSet_to_mae(obj)

listOfmatrix_to_mae(obj)

listOfdf_to_mae(obj)

Arguments

`obj`	An object compliant with the formats accepted by `omXplore`
`ll`	A list
`colData`	A data.frame()
`se`	AN instance of the class `SummarizedExperiment`

Value

An enriched instance of the class MultiAssayExperiment

An instance of SimpleList

An enriched instance of the class MultiAssayExperiment

A boolean(1)

An enriched instance of the class SummarizedExperiment

A boolean(1)

An enriched instance of the class MultiAssayExperiment

A boolean(1)

An enriched instance of the class SummarizedExperiment

An enriched instance of the class MultiAssayExperiment

Examples



#-------------------------------------------
# Conversion of a MultiAssayExperiment instance
#-------------------------------------------
data(miniACC, package = 'MultiAssayExperiment')
convert_to_mae(miniACC)


#-------------------------------------------
# Conversion of a MultiAssayExperiment instance
#-------------------------------------------
data(miniACC, package = 'MultiAssayExperiment')
convert_to_mae(miniACC)

Displays a correlation matrix of the quantitative data of a numeric matrix.

Description

Displays a correlation matrix of the quantitative data of a numeric matrix.

Usage

omXplore_corrmatrix_ui(id)

omXplore_corrmatrix_server(
  id,
  obj = reactive({
     NULL
 }),
  i = reactive({
     NULL
 })
)

corrMatrix(data, rate = 0.5, showValues = FALSE)

omXplore_corrmatrix(obj, i)
omXplore_corrmatrix_ui(id)

omXplore_corrmatrix_server(
  id,
  obj = reactive({
     NULL
 }),
  i = reactive({
     NULL
 })
)

corrMatrix(data, rate = 0.5, showValues = FALSE)

omXplore_corrmatrix(obj, i)

Arguments

`id`	A `character(1)` which is the id of the shiny module.
`obj`	An instance of the class `SummarizedExperiment`
`i`	An integer which is the index of the assay in the param obj
`data`	An object of class 'matrix'
`rate`	The rate parameter to control the exponential law for the gradient of colors
`showValues`	A boolean which indicates whether to show values in the correlation plot.

Value

A plot

A shiny app

Examples

if (interactive()) {
  data(vdata)
  omXplore_corrmatrix(vdata, 1)
}

if (interactive()) {
  data(vdata)
  omXplore_corrmatrix(vdata, 1)
}

Customised resetZoom Button of highcharts plots

Description

Customised resetZoom Button of highcharts plots

Usage

customChart(
  hc,
  chartType = "scatter",
  zoomType = "None",
  width = 0,
  height = 0
)
customChart(
  hc,
  chartType = "scatter",
  zoomType = "None",
  width = 0,
  height = 0
)

Arguments

`hc`	A highcharter object
`chartType`	The type of the plot
`zoomType`	The type of the zoom (one of "x", "y", "xy", "None")
`width`	The width of the plot
`height`	The height of the plot

Value

A highchart plot

Author(s)

Samuel Wieczorek

Examples


library(highcharter)
  hc <- highchart()
  hc_chart(hc, type = "line")
  hc_add_series(hc, data = c(29, 71, 40))
  customChart(hc)

library(highcharter)
  hc <- highchart()
  hc_chart(hc, type = "line")
  hc_add_series(hc, data = c(29, 71, 40))
  customChart(hc)

#' @title Customised contextual menu of highcharts plots

Description

#' @title Customised contextual menu of highcharts plots

Usage

customExportMenu(hc, fname)
customExportMenu(hc, fname)

Arguments

`hc`	A highcharter object
`fname`	The filename under which the plot has to be saved

Value

A contextual menu for highcharts plots

Author(s)

Samuel Wieczorek

Examples

NULL

NULL

Displays a correlation matrix of the quantitative data of a numeric matrix.

Description

Displays a correlation matrix of the quantitative data of a numeric matrix.

Usage

omXplore_density_ui(id)

omXplore_density_server(
  id,
  obj = reactive({
     NULL
 }),
  i = reactive({
     NULL
 }),
  pal.name = reactive({
     NULL
 })
)

densityPlot(data, conds = NULL, pal.name = NULL)

omXplore_density(obj, i)
omXplore_density_ui(id)

omXplore_density_server(
  id,
  obj = reactive({
     NULL
 }),
  i = reactive({
     NULL
 }),
  pal.name = reactive({
     NULL
 })
)

densityPlot(data, conds = NULL, pal.name = NULL)

omXplore_density(obj, i)

Arguments

`id`	A `character(1)` which is the id of the shiny module.
`obj`	An instance of the class `SummarizedExperiment`
`i`	An integer which is the index of the assay in the param obj
`pal.name`	A `character(1)` which is the name of the palette from the package RColorBrewer from which the colors are taken. Default value is 'Set1'.
`data`	A data.frame() of quantitative data
`conds`	A vector indicating the name of each sample.

Value

A plot

A shiny app

Examples


  data(vdata)
  omXplore_density(vdata, 1)

data(vdata)
qdata <- SummarizedExperiment::assay(vdata[[1]])
conds <- get_group(vdata)
densityPlot(qdata, conds)

data(vdata)
  omXplore_density(vdata, 1)

data(vdata)
qdata <- SummarizedExperiment::assay(vdata[[1]])
conds <- get_group(vdata)
densityPlot(qdata, conds)

Bar plot of missing values per lines using highcharter.

Description

This method plots a bar plot which represents the distribution of the number of missing values (NA) per lines (ie proteins).

wrapper_pca()
plotPCA_Eigen_hc(): plots the eigen values of PCA with the highcharts library
plotPCA_Eigen(): plots the eigen values of PCA
plotPCA_Var()
plotPCA_Ind()

Usage

omXplore_pca_ui(id)

omXplore_pca_server(id, obj, i)

omXplore_pca(obj, i)

wrapper_pca(qdata, group, var.scaling = TRUE, ncp = NULL)

plotPCA_Eigen(res.pca)

plotPCA_Var(res.pca, chosen.axes = c(1, 2))

plotPCA_Ind(res.pca, chosen.axes = c(1, 2))

plotPCA_Eigen_hc(res.pca)
omXplore_pca_ui(id)

omXplore_pca_server(id, obj, i)

omXplore_pca(obj, i)

wrapper_pca(qdata, group, var.scaling = TRUE, ncp = NULL)

plotPCA_Eigen(res.pca)

plotPCA_Var(res.pca, chosen.axes = c(1, 2))

plotPCA_Ind(res.pca, chosen.axes = c(1, 2))

plotPCA_Eigen_hc(res.pca)

Arguments

`id`	A `character(1)` which is the id of the shiny module.
`obj`	An instance of the class `MultiAssayExperiment`.
`i`	An integer which is the index of the assay in the param obj
`qdata`	A data.frame() of quantitative data
`group`	A vector with the name of samples
`var.scaling`	A boolean indicating whether to scale the data or not
`ncp`	See `FactoMineR::PCA()`
`res.pca`	The result of the function `FactoMineR::PCA()`
`chosen.axes`	See the parameter 'axes' of the function `factoextra::fviz_pca_var()`

Value

A shiny app

The result of the function FactoMineR::PCA()

A plot

Author(s)

Samuel Wieczorek, Enora Fremy

Examples


  data(vdata)
  # Replace missing values for the example
  sel <- is.na(SummarizedExperiment::assay(vdata, 1))
  SummarizedExperiment::assay(vdata[[1]])[sel] <- 0
  omXplore_pca(vdata, 1)

data(vdata)
obj <- vdata[[1]]
res.pca <- wrapper_pca(SummarizedExperiment::assay(obj), get_group(obj))
plotPCA_Eigen(res.pca)
plotPCA_Var(res.pca)
plotPCA_Eigen_hc(res.pca)
plotPCA_Ind(res.pca)

data(vdata)
  # Replace missing values for the example
  sel <- is.na(SummarizedExperiment::assay(vdata, 1))
  SummarizedExperiment::assay(vdata[[1]])[sel] <- 0
  omXplore_pca(vdata, 1)

data(vdata)
obj <- vdata[[1]]
res.pca <- wrapper_pca(SummarizedExperiment::assay(obj), get_group(obj))
plotPCA_Eigen(res.pca)
plotPCA_Var(res.pca)
plotPCA_Eigen_hc(res.pca)
plotPCA_Ind(res.pca)

Bar plot of missing values per lines using `highcharter`.

Description

This method plots a bar plot which represents the distribution of the number of missing values (NA) per lines (i.e. proteins).

Usage

view_dataset_ui(id)

view_dataset_server(
  id,
  obj = reactive({
     NULL
 }),
  addons = list(),
  useModal = TRUE,
  verbose = FALSE
)

view_dataset(obj = NULL, addons = NULL, useModal = TRUE)
view_dataset_ui(id)

view_dataset_server(
  id,
  obj = reactive({
     NULL
 }),
  addons = list(),
  useModal = TRUE,
  verbose = FALSE
)

view_dataset(obj = NULL, addons = NULL, useModal = TRUE)

Arguments

`id`	A `character(1)` for the 'id' of the shiny module. It must be the same as for the '*_ui' function.
`obj`	An instance of the class `MultiAssayExperiment`.
`addons`	A `list` to configure the other shiny apps to integrate. Each item correspond to one package: the name of the slot is the name of the package the content of the slot is a vector composed of the generic name of the shiny app. Each of the apps listed here must be an exported app of the package. For example, given the value addons = list(testPkg = c('foo', 'foo2')). That means that the package called "testPkg" must provide the four functions: foo1_ui(), foo1_server() and foo2_ui(), foo2_server())
`useModal`	A `boolean(1)` that indicates whether to open plot modules in a modal window or not. Default is TRUE.
`verbose`	A boolean for verbose mode. Default is FALSE.

Details

distribution of the missing values per line,
a bar plot which represents the distribution of the number of missing values (NA) per lines (i.e. proteins) and per conditions,
Histogram of missing values.
Variance : Builds a densityplot of the CV of entities in numeric matrix. The CV is calculated for each condition present in the dataset (see the slot 'Condition' in the colData() DataFrame)
Heatmap:

The function heatmapD()

The function [] is inspired from the function 'heatmap.2' that displays a numeric matrix. For more information, please refer to the help of the heatmap.2 function.

Value

A shiny application which wraps the functions view_dataset_ui() and the view_dataset_server()

Missing values

#' - distribution of the missing values per line,

a bar plot which represents the distribution of the number of missing values (NA) per lines (ie proteins) and per conditions,
Histogram of missing values.

Author(s)

Samuel Wieczorek, Enora Fremy

Examples


  data(vdata)
  addons <- list(omXplore = c("extFoo1", "extFoo2"))
  runApp(view_dataset(vdata, addons))
  
  shiny::runApp(view_dataset(vdata))

if (interactive()) {
  data(vdata)
  view_dataset(vdata)
}

data(vdata)
  addons <- list(omXplore = c("extFoo1", "extFoo2"))
  runApp(view_dataset(vdata, addons))
  
  shiny::runApp(view_dataset(vdata))

if (interactive()) {
  data(vdata)
  view_dataset(vdata)
}

External module example

Description

Example for an external shiny module, well structured to be run within a workflow for MagellanNTK

Usage

extFoo1_ui(id)

extFoo1_server(
  id,
  obj = reactive({
     NULL
 }),
  i = reactive({
     NULL
 })
)

extFoo1(obj, i)

extFoo2_ui(id)

extFoo2_server(
  id,
  obj = reactive({
     NULL
 }),
  i = reactive({
     NULL
 })
)

extFoo2(obj, i)
extFoo1_ui(id)

extFoo1_server(
  id,
  obj = reactive({
     NULL
 }),
  i = reactive({
     NULL
 })
)

extFoo1(obj, i)

extFoo2_ui(id)

extFoo2_server(
  id,
  obj = reactive({
     NULL
 }),
  i = reactive({
     NULL
 })
)

extFoo2(obj, i)

Arguments

`id`	A `character(1)` which is the id of the shiny module.
`obj`	An object of instance `MultiAssayExperiment`
`i`	An integer which is the index of the assay in the param obj

Value

A shiny app

Examples

if (interactive()) {
  data(vdata)
  app1 <- extFoo1(vdata, 1)
  app2 <- extFoo2(vdata, 1)
  shiny::runApp(app1)
  shiny::runApp(app2)
}

if (interactive()) {
  data(vdata)
  app1 <- extFoo1(vdata, 1)
  app2 <- extFoo2(vdata, 1)
  shiny::runApp(app1)
  shiny::runApp(app2)
}

formatDT_ui and formatDT_server

Description

A shiny Module.

See DT package homepage for more details about styling tables. If no style is precised, this module show the raw data. If any style is given, then the dataset must be well configured (I.e. it must contain the correct columns )

Usage

formatDT_ui(id)

formatDT_server(
  id,
  data = reactive({
     NULL
 }),
  data_nostyle = reactive({
     NULL
 }),
  withDLBtns = FALSE,
  showRownames = FALSE,
  dt_style = reactive({
     NULL
 }),
  filename = "Prostar_export",
  selection = "single"
)

formatDT(data)
formatDT_ui(id)

formatDT_server(
  id,
  data = reactive({
     NULL
 }),
  data_nostyle = reactive({
     NULL
 }),
  withDLBtns = FALSE,
  showRownames = FALSE,
  dt_style = reactive({
     NULL
 }),
  filename = "Prostar_export",
  selection = "single"
)

formatDT(data)

Arguments

`id`	shiny id
`data`	A `data.frame`
`data_nostyle`	A data.frame() to be bind to the main data with no custom style
`withDLBtns`	A boolean to indicate whether to display download buttons or not.
`showRownames`	A boolean to indicate whether to show rownames.
`dt_style`	A `list` composed of: data : a data.frame colors : a named vector
`filename`	A `character(1)` which is the default filename for download.
`selection`	A `character(1)` which indicates the type of selection. Default is 'single'.

Value

Examples

if (interactive()) {
  data(vdata)
  formatDT(SummarizedExperiment::assay(vdata, 1))
}

if (interactive()) {
  data(vdata)
  formatDT(SummarizedExperiment::assay(vdata, 1))
}

Constructs a dataset suitable to use with the module format_DT.

Description

This function builds the skeleton of a dataset which can be used by the module formatDT. It creates additional columns to be used to style the table. to colors cells.

Usage

FormatDataForDT(se, digits = 2)
FormatDataForDT(se, digits = 2)

Arguments

`se`	An instance of the class `SummarizedExperiment`
`digits`	An 'integer(1)' to specify the number of digits to display in the tables for numerical values. Default is 2.

Value

A data.frame

Package version

Description

Gets the version number of a package

Usage

GetPkgVersion(pkg)
GetPkgVersion(pkg)

Arguments

pkg

The name of the package

Value

A character(1) with the name of the package and its version number.

Examples

GetPkgVersion('omXplore')

GetPkgVersion('omXplore')

Global variables

Description

Defines the global variables for the package omXplore

Usage

globals()
globals()

Value

A list

Examples

globals()

globals()

Displays different intensity plots.

Description

Displays different intensity plots.

Usage

omXplore_intensity_ui(id)

omXplore_intensity_server(
  id,
  obj,
  i,
  track.indices = reactive({
     NULL
 }),
  remoteReset = reactive({
     NULL
 }),
  is.enabled = reactive({
     TRUE
 })
)

omXplore_intensity(obj, i, withTracking = FALSE)

boxPlot(obj, conds, legend = NULL, pal = NULL, subset = NULL)

violinPlot(data, conds, subset = NULL, pal.name = "Set1")
omXplore_intensity_ui(id)

omXplore_intensity_server(
  id,
  obj,
  i,
  track.indices = reactive({
     NULL
 }),
  remoteReset = reactive({
     NULL
 }),
  is.enabled = reactive({
     TRUE
 })
)

omXplore_intensity(obj, i, withTracking = FALSE)

boxPlot(obj, conds, legend = NULL, pal = NULL, subset = NULL)

violinPlot(data, conds, subset = NULL, pal.name = "Set1")

Arguments

`id`	A `character(1)` which is the id of the shiny module.
`obj`	A instance of the class `MultiAssayExperiment`
`i`	An integer which is the index of the assay in the param obj
`track.indices`	A vector of integers which are the indices of lines to track.
`withTracking`	A `boolean(1)` indicating whether the tracking option is activated or not.
`conds`	A vector indicating the name of each sample.
`legend`	A vector of the conditions (one condition per sample).
`pal`	A basis palette for the boxes which length must be equal to the number of unique conditions in the dataset.
`subset`	A `integer()` vector of index indicating the indices of rows in the dataset to highlight
`data`	A data.frame() of quantitaive data
`pal.name`	A `character(1)` which is the name of the palette from the package RColorBrewer from which the colors are taken. Default value is 'Set1'.

Value

A shiny app

A boxplot

A violin plot

Author(s)

Samuel Wieczorek, Anais Courtier, Enora Fremy

Examples


  data(vdata)
  shiny::runApp(omXplore_intensity(vdata, 1))
  
data(sub_R25)
conds <- legend <- SummarizedExperiment::colData(sub_R25)$group
pal <- ExtendPalette(length(unique(conds)))
boxPlot(sub_R25[[1]], conds, legend, pal, seq_len(10))


data(vdata)
  shiny::runApp(omXplore_intensity(vdata, 1))
  
data(sub_R25)
conds <- legend <- SummarizedExperiment::colData(sub_R25)$group
pal <- ExtendPalette(length(unique(conds)))
boxPlot(sub_R25[[1]], conds, legend, pal, seq_len(10))

Checks the class of a list's slots

Description

Checks if all slots of the given list are of the same class.

Usage

is.listOf(object, obj.class = NULL)
is.listOf(object, obj.class = NULL)

Arguments

`object`	A `list`
`obj.class`	The name of the class to search in items of the list.

Value

A character(1) with the name of the package or NULL

Examples

ll <- as.list(LETTERS[1:3])
is.listOf(ll, "data.frame")
is.listOf(ll, "character")

ll <- as.list(LETTERS[1:3])
is.listOf(ll, "data.frame")
is.listOf(ll, "character")

Displays a correlation matrix of the quantitative data of a numeric matrix.

Description

This function is a wrapper to heatmap.2() that displays assay data in an instance of SummarizedExperiment. For more details, see heatmap.2().

Usage

omXplore_heatmap_ui(id)

omXplore_heatmap_server(
  id,
  obj = reactive({
     NULL
 }),
  i = reactive({
     NULL
 })
)

omXplore_heatmap(obj, i)

heatmapD(
  qdata,
  conds,
  distance = "euclidean",
  cluster = "complete",
  dendro = FALSE
)

mv.heatmap(
  x,
  col = grDevices::heat.colors(100),
  srtCol = NULL,
  labCol = NULL,
  labRow = NULL,
  key = TRUE,
  key.title = NULL,
  main = NULL,
  ylab = NULL
)

heatmapForMissingValues(
  x,
  col = NULL,
  srtCol = NULL,
  labCol = NULL,
  labRow = NULL,
  key = TRUE,
  key.title = NULL,
  main = NULL,
  ylab = NULL
)
omXplore_heatmap_ui(id)

omXplore_heatmap_server(
  id,
  obj = reactive({
     NULL
 }),
  i = reactive({
     NULL
 })
)

omXplore_heatmap(obj, i)

heatmapD(
  qdata,
  conds,
  distance = "euclidean",
  cluster = "complete",
  dendro = FALSE
)

mv.heatmap(
  x,
  col = grDevices::heat.colors(100),
  srtCol = NULL,
  labCol = NULL,
  labRow = NULL,
  key = TRUE,
  key.title = NULL,
  main = NULL,
  ylab = NULL
)

heatmapForMissingValues(
  x,
  col = NULL,
  srtCol = NULL,
  labCol = NULL,
  labRow = NULL,
  key = TRUE,
  key.title = NULL,
  main = NULL,
  ylab = NULL
)

Arguments

`id`	A `character(1)` which is the id of the shiny module.
`obj`	An instance of a class `MultiAssayExperiment`.
`i`	An integer which is the index of the assay in the param obj
`qdata`	A data.frame() of quantitative data.
`conds`	A vector indicating the name of each sample.
`distance`	The distance used by the clustering algorithm to compute the dendrogram.
`cluster`	the clustering algorithm used to build the dendrogram.
`dendro`	A boolean to indicate fi the dendrogram has to be displayed
`x`	A `matrix` or `array` containing the quantitative data.
`col`	Colors used for the image. Defaults to heat colors (heat.colors).
`srtCol`	Angle of column conds, in degrees from horizontal
`labCol`	Character vectors with column conds to use.
`labRow`	Character vectors with row conds to use.
`key`	Logical indicating whether a color-key should be shown.
`key.title`	Main title of the color key. If set to NA no title will be plotted.
`main`	Main title; default to none.
`ylab`	y-axis title; default to none.

Value

A shiny app

A heatmap

Author(s)

Florence Combes, Samuel Wieczorek, Enora Fremy

Examples


  data(vdata)
  omXplore_heatmap(vdata, 1)

data(vdata)
  omXplore_heatmap(vdata, 1)

Explore `MultiAssayExperiment` objects.

Description

Explore MultiAssayExperiment objects.

Usage

omXplore_tabExplorer_ui(id)

omXplore_tabExplorer_server(
  id,
  obj = reactive({
     NULL
 }),
  i = reactive({
     NULL
 }),
  digits = reactive({
     3
 })
)

omXplore_tabExplorer(obj, i)
omXplore_tabExplorer_ui(id)

omXplore_tabExplorer_server(
  id,
  obj = reactive({
     NULL
 }),
  i = reactive({
     NULL
 }),
  digits = reactive({
     3
 })
)

omXplore_tabExplorer(obj, i)

Arguments

`id`	A `character(1)` which is the id of the shiny module.
`obj`	An instance of the class `MultiAssayExperiment`
`i`	An integer which is the index of the assay in the param obj
`digits`	An integer for the number of digits shown in the table

Value

A shiny app

Examples


  data(vdata)
  shiny::runApp(omXplore_tabExplorer(vdata, 1))

data(vdata)
  shiny::runApp(omXplore_tabExplorer(vdata, 1))

Shiny modules used by `omXplore`

Description

These functions are relative to external modules that can be added into omXplore UI:

listShinyApps(): Show the shiny modules recognized by omXplore and ready to bu integrated in the UI of the function view_dataset()
listPlotModules(): Show the shiny modules function names (only prefixes) recognized by omXplore and ready to use in the UI.
addModules(): Add external shiny module(s) to the R global environment in such a way (specific prefix renaming of the functions) that it can be discovered by the function view_dataset() of the package omXplore during its launch.

Usage

addModules(addons = list())

listShinyApps(location = "both")

listPlotModules(location = "both")
addModules(addons = list())

listShinyApps(location = "both")

listPlotModules(location = "both")

Arguments

addons

A list in which each item:

is named by the name of a package containing the modules to add,
contains the name of the shiny modules to integrate (without '_ui' nor '_server' suffixes)

location

A character(0) to indicate which modules to list. Available values are: 'builtin', 'external' and 'both' (default).

Value

A vector

Examples

listShinyApps()
listPlotModules()

#####################################################
# Integration of a module in the package 'mypackage'
#####################################################

addons <- list(omXplore = c("extFoo1", "extFoo2"))
addModules(addons)


listShinyApps()
listPlotModules()

#####################################################
# Integration of a module in the package 'mypackage'
#####################################################

addons <- list(omXplore = c("extFoo1", "extFoo2"))
addModules(addons)

Palette for samples.

Description

Builds a vector of ⁠#conditions⁠ colors for a set of samples. One color is given for a given condition. This function extends a base palette from the package RColorBrewer to 'n' colors. The colors in the returned palette are always in the same order

Usage

SampleColors(conds, pal.name = "Set1")

ExtendPalette(n, pal.name = "Set1")

GetColorsForConditions(conds, pal = NULL)
SampleColors(conds, pal.name = "Set1")

ExtendPalette(n, pal.name = "Set1")

GetColorsForConditions(conds, pal = NULL)

Arguments

`conds`	A `character()` of conditions. The length of the vector is the number of samples in the dataset.
`pal.name`	A `character(1)` which is the name of the palette from the package RColorBrewer from which the colors are taken. Default value is 'Set1'.
`n`	The number of desired colors in the palette
`pal`	A vector of HEX color code that form the basis palette from which to build the complete color vector for the conditions.

Value

A vector

Examples


#-----------------------------------------------
# Builds a palette for a dataset with 3 conditions
# of 3 samples each.
#------------------------------------------------

conds <- c(rep("A", 3), rep("B", 3), rep("C", 3))
SampleColors(conds)
SampleColors(conds, "Dark2")


#-----------------------------------------------
# Extend the default palette to 12 colors
#-----------------------------------------------

ExtendPalette(12)


data(vdata)
conds <- get_group(vdata)
GetColorsForConditions(conds, ExtendPalette(2))

#-----------------------------------------------
# Builds a palette for a dataset with 3 conditions
# of 3 samples each.
#------------------------------------------------

conds <- c(rep("A", 3), rep("B", 3), rep("C", 3))
SampleColors(conds)
SampleColors(conds, "Dark2")


#-----------------------------------------------
# Extend the default palette to 12 colors
#-----------------------------------------------

ExtendPalette(12)


data(vdata)
conds <- get_group(vdata)
GetColorsForConditions(conds, ExtendPalette(2))

Display a CC

Description

Display a CC

Connected Components infos

Usage

buildGraph(cc = NULL, meta = NULL)

display.CC.visNet(g = NULL, layout = "layout_with_fr")

plotCCJitter(df, clickFunction = NULL)

GetCCInfos(cc)
buildGraph(cc = NULL, meta = NULL)

display.CC.visNet(g = NULL, layout = "layout_with_fr")

plotCCJitter(df, clickFunction = NULL)

GetCCInfos(cc)

Arguments

`cc`	A list of connected component
`meta`	A data.frame()
`g`	An instance of a graph
`layout`	A `character(1)` which i the layout used in visNetwork. Default value is 'layout_with_fr'
`df`	A data.frame()
`clickFunction`	A JS function to determine the behaviour of a click

Value

A list

A plot

A list of three items:

One_One: the number of cc composed of one protein and one peptide
One_Multi: the number of cc composed of one protein and several peptides
Multi_Multi: the number of cc composed of several proteins and several (shared) peptides.

Author(s)

Thomas Burger, Samuel Wieczorek

Examples

data(sub_R25)
se <- sub_R25[[1]]
g <- buildGraph(get_cc(se)[[1]])
display.CC.visNet(g)

data(sub_R25)
GetCCInfos(get_cc(sub_R25[[1]]))

data(sub_R25)
se <- sub_R25[[1]]
g <- buildGraph(get_cc(se)[[1]])
display.CC.visNet(g)

data(sub_R25)
GetCCInfos(get_cc(sub_R25[[1]]))

Loads packages

Description

Checks if a package is available to load it

Usage

pkgs.require(ll.deps)
pkgs.require(ll.deps)

Arguments

ll.deps

A character() vector which contains packages names

Value

Author(s)

Samuel Wieczorek

Examples

pkgs.require('omXplore')

pkgs.require('omXplore')

Variance plot

Description

A shiny module which plots the variance of samples

Usage

omXplore_variance_ui(id)

omXplore_variance_server(id, obj, i, pal.name = NULL)

CVDist(obj, conds, pal.name = NULL)

omXplore_variance(obj, i)
omXplore_variance_ui(id)

omXplore_variance_server(id, obj, i, pal.name = NULL)

CVDist(obj, conds, pal.name = NULL)

omXplore_variance(obj, i)

Arguments

`id`	A `character(1)` which is the id of the shiny module.
`obj`	An matrix
`i`	An integer which is the index of the assay in the param obj
`pal.name`	A `character(1)` which is the name of the palette from the package RColorBrewer from which the colors are taken. Default value is 'Set1'.
`conds`	A vector indicating the name of each sample.

Value

A plot

A shiny app

Examples

if (interactive()) {
  data(vdata)
  omXplore_variance(vdata, 1)
}

if (interactive()) {
  data(vdata)
  omXplore_variance(vdata, 1)
}

Convert datasets exported by the package `Prostar`

Description

Convert datasets exported by the package Prostar

Usage

SE_Compatibility_with_Prostar_1.x(obj, se)

MAE_Compatibility_with_Prostar_1x(obj, mae)
SE_Compatibility_with_Prostar_1.x(obj, se)

MAE_Compatibility_with_Prostar_1x(obj, mae)

Arguments

`obj`	An instance of the class `MSnSet`
`se`	An instance of the class `SummarizedExperiment`
`mae`	An instance of the class `MultiAssayExperiment`

Value

An enriched instance of the class SummarizedExperiment

An enriched instance of the class MultiAssayExperiment

Examples

data(sub_R25)



data(sub_R25)

Quantitative metadata vocabulary for entities

Description

This function gives the vocabulary used for the quantitative metadata of each entity in each condition.

Usage

metacell.def(level)

Parent(level, node = NULL)

Children(level, parent = NULL)

GetMetacellTags(metacells = NULL, level = NULL, onlyPresent = FALSE)
metacell.def(level)

Parent(level, node = NULL)

Children(level, parent = NULL)

GetMetacellTags(metacells = NULL, level = NULL, onlyPresent = FALSE)

Arguments

`level`	A string corresponding to the type of object
`node`	The name of the node for which one wants its parent #' @examples Parent('protein', 'Missing') Parent('protein', 'Missing POV') Parent('protein', c('Missing POV', 'Missing MEC')) Parent('protein', c('Missing', 'Missing POV', 'Missing MEC'))
`parent`	The name og the parent node
`metacells`	A data.frame() representing the cell metadata
`onlyPresent`	A `boolean(1)`

Value

A data.frame containing the different tags and corresponding colors for the level given in parameter

A list

A vector

Glossary

Peptide-level vocabulary

Conversion to the glossary

A generic conversion

Conversion for Proline datasets

Conversion from Maxquant datasets

Author(s)

Thomas Burger, Samuel Wieczorek

Samuel Wieczorek

Examples


metacell.def("protein")
metacell.def("peptide")

#-----------------------------------------------
# A shiny app to view color legends
#-----------------------------------------------
if(interactive()) {
  data(vdata)
  ui <- qMetacellLegend_ui("legend")

  server <- function(input, output, session) {
    qMetacellLegend_server("legend",
      object = reactive({vdata[[1]]})
    )
  }

  shinyApp(ui = ui, server = server)
}

Children("protein", "Missing")
Children("protein", "Missing POV")
Children("protein", c("Missing POV", "Missing MEC"))
Children("protein", c("Missing", "Missing POV", "Missing MEC"))
data(vdata)
metacells <- get_metacell(vdata[[1]])
level <- get_type(vdata[[1]])
GetMetacellTags(metacells, level)

metacell.def("protein")
metacell.def("peptide")

#-----------------------------------------------
# A shiny app to view color legends
#-----------------------------------------------
if(interactive()) {
  data(vdata)
  ui <- qMetacellLegend_ui("legend")

  server <- function(input, output, session) {
    qMetacellLegend_server("legend",
      object = reactive({vdata[[1]]})
    )
  }

  shinyApp(ui = ui, server = server)
}

Children("protein", "Missing")
Children("protein", "Missing POV")
Children("protein", c("Missing POV", "Missing MEC"))
Children("protein", c("Missing", "Missing POV", "Missing MEC"))
data(vdata)
metacells <- get_metacell(vdata[[1]])
level <- get_type(vdata[[1]])
GetMetacellTags(metacells, level)

Feature example data

Description

sub_R25 is a protein subset of the dataset 'Exp1_R25_pept' in the package DAPARdata.

Format

An instance of the class MultiAssayExperiment

Value

An enriched instance of the class MultiAssayExperiment

Source

sub_R25 was built from the source code available in inst/scripts/build_datasets.R

The DAPARdata package: https://github.com/prostarproteomics/DAPARdata

Feature example data

Description

vdata is a small object for testing and demonstration.

Format

An instance of the class MultiAssayExperiment

Value

An enriched instance of the class MultiAssayExperiment

Source

vdata was built from the source code available in inst/scripts/build_datasets.R