romanhaa/cerebroApp
Interactive visualization of scRNA-seq data with Cerebro

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Cerebro_v1.3: R6 class in which data sets will be stored for visualization...

Cerebro_v1.3: R6 class in which data sets will be stored for visualization...
In romanhaa/cerebroApp: Interactive visualization of scRNA-seq data with Cerebro

Description Value Public fields Methods

Description

A Cerebro_v1.3 object is an R6 class that contains several types of data that can be visualized in Cerebro.

Value

A new Cerebro_v1.3 object.

Public fields

version

cerebroApp version that was used to create the object.

experiment

list that contains meta data about the data set, including experiment name, species, date of export.

technical_info

list that contains technical information about the analysis, including the R session info.

parameters

list that contains important parameters that were used during the analysis, e.g. cut-off values for cell filtering.

groups

list that contains specified grouping variables and and the group levels (subgroups) that belong to each of them. For each grouping variable, a corresponding column with the same name must exist in the meta data.

cell_cycle

vector that contains the name of columns in the meta data that contain cell cycle assignments.

gene_lists

list that contains gene lists, e.g. mitochondrial and/or ribosomal genes.

expression

matrix-like object that holds transcript counts.

meta_data

data.frame that contains cell meta data.

projections

list that contains projections/dimensional reductions.

most_expressed_genes

list that contains a data.frame holding the most expressed genes for each grouping variable that was specified during the call to getMostExpressedGenes.

marker_genes

list that contains a list for every method that was used to calculate marker genes, and a data.frame for each grouping variable, e.g. those that were specified during the call to getMarkerGenes.

enriched_pathways

list that contains a list for every method that was used to calculate marker genes, and a data.frame for each grouping variable, e.g. those that were specified during the call to getEnrichedPathways or performGeneSetEnrichmentAnalysis.

trees

list that contains a phylogenetic tree (class phylo) for grouping variables.

trajectories

list that contains a list for every method that was used to calculate trajectories, and, depending on the method, a data.frame or list for each specific trajectory, e.g. those extracted with extractMonocleTrajectory.

extra_material

list that can contain additional material related to the data set; tables should be stored in data.frame format in a named list called 'tables'

Methods

Public methods

Method new()

Create a new Cerebro_v1.3 object.

Usage
Cerebro_v1.3$new()
Returns

A new Cerebro_v1.3 object.

Method setVersion()

Set the version of cerebroApp that was used to generate this object.

Usage
Cerebro_v1.3$setVersion(version)
Arguments
version

Version to set.

Method getVersion()

Get the version of cerebroApp that was used to generate this object.

Usage
Cerebro_v1.3$getVersion()
Returns

Version as package_version class.

Method checkIfGroupExists()

Safety function that will check if a provided group name is present in the groups field.

Usage
Cerebro_v1.3$checkIfGroupExists(group_name)
Arguments
group_name

Group name to be tested

Method checkIfColumnExistsInMetadata()

Safety function that will check if a provided group name is present in the meta data.

Usage
Cerebro_v1.3$checkIfColumnExistsInMetadata(group_name)
Arguments
group_name

Group name to be tested.

Method addExperiment()

Add information to experiment field.

Usage
Cerebro_v1.3$addExperiment(field, content)
Arguments
field

Name of the information, e.g. organism.

content

Actual information, e.g. hg.

Method getExperiment()

Retrieve information from experiment field.

Usage
Cerebro_v1.3$getExperiment()
Returns

list of all entries in the experiment field.

Method addParameters()

Add information to parameters field.

Usage
Cerebro_v1.3$addParameters(field, content)
Arguments
field

Name of the information, e.g. number_of_PCs.

content

Actual information, e.g. 30.

Method getParameters()

Retrieve information from parameters field.

Usage
Cerebro_v1.3$getParameters()
Returns

list of all entries in the parameters field.

Method addTechnicalInfo()

Add information to technical_info field.

Usage
Cerebro_v1.3$addTechnicalInfo(field, content)
Arguments
field

Name of the information, e.g. R.

content

Actual information, e.g. 4.0.2.

Method getTechnicalInfo()

Retrieve information from technical_info field.

Usage
Cerebro_v1.3$getTechnicalInfo()
Returns

list of all entries in the technical_info field.

Method addGroup()

Add group to the groups registered in the groups field.

Usage
Cerebro_v1.3$addGroup(group_name, levels)
Arguments
group_name

Group name.

levels

vector of group levels (subgroups).

Method getGroups()

Retrieve all names in the groups field.

Usage
Cerebro_v1.3$getGroups()
Returns

vector of registered groups.

Method getGroupLevels()

Retrieve group levels for a group registered in the groups field.

Usage
Cerebro_v1.3$getGroupLevels(group_name)
Arguments
group_name

Group name for which to retrieve group levels.

Returns

vector of group levels.

Method setMetaData()

Set meta data for cells.

Usage
Cerebro_v1.3$setMetaData(table)
Arguments
table

data.frame that contains meta data for cells. The number of rows must be equal to the number of rows of projections and the number of columns in the transcript count matrix.

Method getMetaData()

Retrieve meta data for cells.

Usage
Cerebro_v1.3$getMetaData()
Returns

data.frame containing meta data.

Method addGeneList()

Add a gene list to the gene_lists.

Usage
Cerebro_v1.3$addGeneList(name, genes)
Arguments
name

Name of the gene list.

genes

vector of genes.

Method getGeneLists()

Retrieve gene lists from the gene_lists.

Usage
Cerebro_v1.3$getGeneLists()
Returns

list of all entries in the gene_lists field.

Method setExpression()

Set transcript count matrix.

Usage
Cerebro_v1.3$setExpression(counts)
Arguments
counts

matrix-like object that contains transcript counts for cells in the data set. Number of columns must be equal to the number of rows in the meta_data field.

Method getCellNames()

Get names of all cells.

Usage
Cerebro_v1.3$getCellNames()
Returns

vector containing all cell names/barcodes.

Method getGeneNames()

Get names of all genes in transcript count matrix.

Usage
Cerebro_v1.3$getGeneNames()
Returns

vector containing all gene names in transcript count matrix.

Method getMeanExpressionForGenes()

Retrieve mean expression across all cells in the data set for a set of genes.

Usage
Cerebro_v1.3$getMeanExpressionForGenes(genes)
Arguments
genes

Names of genes to extract; no default.

Returns

data.frame containing specified gene names and their respective mean expression across all cells in the data set.

Method getMeanExpressionForCells()

Retrieve (mean) expression for a single gene or a set of genes for a given set of cells.

Usage
Cerebro_v1.3$getMeanExpressionForCells(cells = NULL, genes = NULL)
Arguments
cells

Names/barcodes of cells to extract; defaults to NULL, which will return all cells.

genes

Names of genes to extract; defaults to NULL, which will return all genes.

Returns

vector containing (mean) expression across all specified genes in each specified cell.

Method getExpressionMatrix()

Retrieve transcript count matrix.

Usage
Cerebro_v1.3$getExpressionMatrix(cells = NULL, genes = NULL)
Arguments
cells

Names/barcodes of cells to extract; defaults to NULL, which will return all cells.

genes

Names of genes to extract; defaults to NULL, which will return all genes.

Returns

Dense transcript count matrix for specified cells and genes.

Method setCellCycle()

Add columns containing cell cycle assignments to the cell_cycle field.

Usage
Cerebro_v1.3$setCellCycle(cols)
Arguments
cols

vector of columns names containing cell cycle assignments.

Method getCellCycle()

Retrieve column names containing cell cycle assignments.

Usage
Cerebro_v1.3$getCellCycle()
Returns

vector of column names in meta data.

Method addProjection()

Add projections (dimensional reductions).

Usage
Cerebro_v1.3$addProjection(name, projection)
Arguments
name

Name of the projection.

projection

data.frame containing positions of cells in projection.

Method availableProjections()

Get list of available projections (dimensional reductions).

Usage
Cerebro_v1.3$availableProjections()
Returns

vector of projections / dimensional reductions that are available.

Method getProjection()

Retrieve data for a specific projection.

Usage
Cerebro_v1.3$getProjection(name)
Arguments
name

Name of projection.

Returns

data.frame containing the positions of cells in the projection.

Method addTree()

Add phylogenetic tree to trees field.

Usage
Cerebro_v1.3$addTree(group_name, tree)
Arguments
group_name

Group name that this tree belongs to.

tree

Phylogenetic tree as phylo object.

Method getTree()

Retrieve phylogenetic tree for a specific group.

Usage
Cerebro_v1.3$getTree(group_name)
Arguments
group_name

Group name for which to retrieve phylogenetic tree.

Returns

Phylogenetic tree as phylo object.

Method addMostExpressedGenes()

Add table of most expressed genes.

Usage
Cerebro_v1.3$addMostExpressedGenes(group_name, table)
Arguments
group_name

Name of grouping variable that the most expressed genes belong to. Must be registered in the groups field.

table

data.frame that contains the most expressed genes.

Method getGroupsWithMostExpressedGenes()

Retrieve names of grouping variables for which most expressed genes are available.

Usage
Cerebro_v1.3$getGroupsWithMostExpressedGenes()
Returns

vector of grouping variables for which most expressed genes are available.

Method getMostExpressedGenes()

Retrieve table of most expressed genes for a grouping variable.

Usage
Cerebro_v1.3$getMostExpressedGenes(group_name)
Arguments
group_name

Grouping variable for which most expressed genes should be retrieved.

Returns

data.frame that contains most expressed genes for group levels of the specified grouping variable.

Method addMarkerGenes()

Add table of marker genes.

Usage
Cerebro_v1.3$addMarkerGenes(method, name, table)
Arguments
method

Name of method that was used to generate the marker genes.

name

Name of table. This name will be used to select the table in Cerebro. It is recommended to use the grouping variable, e.g. sample.

table

data.frame that contains the marker genes.

Method getMethodsForMarkerGenes()

Retrieve names of methods that were used to generate marker genes.

Usage
Cerebro_v1.3$getMethodsForMarkerGenes()
Returns

vector of names of methods that were used to generate marker genes.

Method getGroupsWithMarkerGenes()

Retrieve grouping variables for which marker genes were generated using a specified method.

Usage
Cerebro_v1.3$getGroupsWithMarkerGenes(method)
Arguments
method

Name of method.

Returns

vector of grouping variables for which marker genes were calculated using the specified method.

Method getMarkerGenes()

Retrieve table of marker genes for specific method and grouping variable.

Usage
Cerebro_v1.3$getMarkerGenes(method, name)
Arguments
method

Name of method.

name

Name of table.

Returns

data.frame that contains marker genes for the specified combination of method and grouping variable.

Method addEnrichedPathways()

Add table of enriched pathways.

Usage
Cerebro_v1.3$addEnrichedPathways(method, name, table)
Arguments
method

Name of method that was used to generate the enriched pathways.

name

Name of table. This name will be used to select the table in Cerebro. It is recommended to use the grouping variable, e.g. sample.

table

data.frame that contains the enriched pathways.

Method getMethodsForEnrichedPathways()

Retrieve names of methods that were used to generate enriched pathways.

Usage
Cerebro_v1.3$getMethodsForEnrichedPathways()
Returns

vector of names of methods that were used to generate enriched pathways.

Method getGroupsWithEnrichedPathways()

Retrieve grouping variables for which enriched pathways were generated using a specified method.

Usage
Cerebro_v1.3$getGroupsWithEnrichedPathways(method)
Arguments
method

Name of method.

Returns

vector of grouping variables for which enriched pathways were calculated using the specified method.

Method getEnrichedPathways()

Retrieve table of enriched pathways for specific method and grouping variable.

Usage
Cerebro_v1.3$getEnrichedPathways(method, name)
Arguments
method

Name of method.

name

Grouping variable.

Returns

data.frame that contains enriched pathways for the specified combination of method and grouping variable.

Method addTrajectory()

Add trajectory.

Usage
Cerebro_v1.3$addTrajectory(method, name, content)
Arguments
method

Name of method that was used to generate the trajectory.

name

Name of the trajectory. This name will be used later in Cerebro to select the trajectory.

content

Relevant data for the trajectory, depending on the method this could be a list holding edges, cell positions, pseudotime, etc.

Method getMethodsForTrajectories()

Retrieve names of methods that were used to generate trajectories.

Usage
Cerebro_v1.3$getMethodsForTrajectories()
Returns

vector of names of methods that were used to generate trajectories.

Method getNamesOfTrajectories()

Retrieve names of available trajectories for a specified method.

Usage
Cerebro_v1.3$getNamesOfTrajectories(method)
Arguments
method

Name of method.

Returns

vector of available trajectory for the specified method.

Method getTrajectory()

Retrieve data for a specific trajectory.

Usage
Cerebro_v1.3$getTrajectory(method, name)
Arguments
method

Name of method.

name

Name of trajectory.

Returns

The type of data depends on the method that was used to generate the trajectory.

Method addExtraMaterial()

Add content to extra material field.

Usage
Cerebro_v1.3$addExtraMaterial(category, name, content)
Arguments
category

Name of category. At the moment, only tables and plots are valid categories. Tables must be in data.frame format and plots must be created with ggplot2.

name

Name of material, will be used to select it in Cerebro.

content

Data that should be added.

Method addExtraTable()

Add table to 'extra_material' slot.

Usage
Cerebro_v1.3$addExtraTable(name, table)
Arguments
name

Name of material, will be used to select it in Cerebro.

table

Table that should be added, must be data.frame.

Method addExtraPlot()

Add plot to 'extra_material' slot.

Usage
Cerebro_v1.3$addExtraPlot(name, plot)
Arguments
name

Name of material, will be used to select it in Cerebro.

plot

Plot that should be added, must be created with ggplot2 (class: ggplot).

Method getExtraMaterialCategories()

Get names of categories for which extra material is available.

Usage
Cerebro_v1.3$getExtraMaterialCategories()
Returns

vector with names of available categories.

Method checkForExtraTables()

Check whether there are tables in the extra materials.

Usage
Cerebro_v1.3$checkForExtraTables()
Returns

logical indicating whether there are tables in the extra materials.

Method getNamesOfExtraTables()

Get names of tables in extra materials.

Usage
Cerebro_v1.3$getNamesOfExtraTables()
Returns

vector containing names of tables in extra materials.

Method getExtraTable()

Get table from extra materials.

Usage
Cerebro_v1.3$getExtraTable(name)
Arguments
name

Name of table.

Returns

Requested table in data.frame format.

Method checkForExtraPlots()

Check whether there are plots in the extra materials.

Usage
Cerebro_v1.3$checkForExtraPlots()
Returns

logical indicating whether there are plots in the extra materials.

Method getNamesOfExtraPlots()

Get names of plots in extra materials.

Usage
Cerebro_v1.3$getNamesOfExtraPlots()
Returns

vector containing names of plots in extra materials.

Method getExtraPlot()

Get plot from extra materials.

Usage
Cerebro_v1.3$getExtraPlot(name)
Arguments
name

Name of plot.

Returns

Requested plot made with ggplot2.

Method print()

Show overview of object and the data it contains. Print overview of available marker gene results for self$print() function. Print overview of available enriched pathway results for self$print() function. Print overview of available trajectories for self$print() function. Print overview of extra material for self$print() function.

Usage
Cerebro_v1.3$print()

Method clone()

The objects of this class are cloneable with this method.

Usage
Cerebro_v1.3$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.


romanhaa/cerebroApp documentation built on Nov. 25, 2021, 5:29 p.m.

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