scRNAseq-class: The scRNAseq class

In ilyessr/conclus: ScRNA-seq Workflow CONCLUS - From CONsensus CLUSters To A Meaningful CONCLUSion

The scRNAseq class

Description

S4 class and the main class used by CONCLUS containing the results of the different steps to analyse rare cell populations.

Slots

experimentName

'character' string representing the name of the experiment.

countMatrix

An 'integer matrix' representing the raw count matrix with reads or unique molecular identifiers (UMIs).

sceNorm

Object of class SingleCellExperiment that contains the colData giving informations about cells and the rowData giving informations about genes. It also contains the normalized count matrix.

species

'character' string representing the species of interest. Currently limited to "mouse" and "human". Other organisms can be added on demand.

outputDirectory

A 'character' string of the path to the root output folder.

tSNEList

List of 'Tsne' objects representing the different tSNE coordinates generated by CONCLUS.

dbscanList

List of 'Dbscan' objects representing the different Dbscan clustering generated by CONCLUS.

suggestedClustersNumber

A number got from the dbscan list representing a suggested clusters number to use in clusterCellsInternal().

cellsSimilarityMatrix

A numeric Matrix defining how many times two cells have been associated to the same cluster across the 84 solutions (by default) of clustering.

clustersSimilarityMatrix

A numeric matrix comparing the robustness of the consensus clusters.

clustersSimiliratyOrdered

A factor representing the clusters ordered by similarity.

markerGenesList

List of data.frames. Each data frame contains the ranked genes of one cluster.

topMarkers

A data frame containing the top 10 (by default) marker genes of each clusters.

genesInfos

A data frame containing informations of the markers genes for each clusters.

Constructor

singlecellRNAseq(experimentName = "character", countMatrix = "matrix", species = "character", outputDirectory = "character")

experimentName: String of the name of the experiment.

countMatrix: Matrix containing the raw counts.

species: 'character' string representing the species of interest. Shoud be mouse or human. Other organisms can be added on demand.

outputDirectory: 'character' string representing the path to the output directory.

Accessors

In the following snippets, x is a scRNAseq object.

getExperimentName(x): Get the name of the experiment.
getCountMatrix(x): Get the count matrix.
getSceNorm(x): Get the SingleCellExperiment object used
getSpecies(x): Get the species.
getOutputDirectory(x): Get the path of the output directory.
getTSNEList(x): Get the list of Tsne objects.
getDbscanList(x): Get the list of Dbscan objects.
getSuggestedClustersNumber(x): Get the suggested clusters number.
getCellsSimilarityMatrix(x): Get the cell similarity matrix.
getClustersSimilarityMatrix(x): Get the cluster similarity matrix.
getClustersSimilarityOrdered(x): Get the clusters ordered by similarity.
getMarkerGenesList(x): Get the list of marker genes by clusters.
getTopMarkers(x): Get the most significant markers by clusters into a data.frame.
getGenesInfos(x): Get a data frame containing informations about marker genes.

Subsetting

In the following snippets, x is a scRNAseq object.

setExperimentName(x): Set the name of the experiment.
setCountMatrix(x): Set the count matrix.
setSceNorm(x): Set the SingleCellExperiment object used.
setSpecies(x): Set the species.
setOutputDirectory(x): Set the path of the output directory.
setTSNEList(x): Set the list of Tsne objects.
setDbscanList(x): Set the list of Dbscan objects.
setCellsSimilarityMatrix(x): Set the cell similarity matrix.
setClustersSimilarityMatrix(x): Set the cluster similarity matrix.
setClustersSimiliratyOrdered(x): Set the clusters ordered by similarity.
setMarkerGenesList(x): Set the list of marker genes by clusters
setTopMarkers(x): Set the most significant markers by clusters.
setGenesInfos(x): Set a data.frame containing informations about the marker genes.

Author(s)

Ilyess Rachedi and Nicolas Descostes

See Also

singlecellRNAseq

ilyessr/conclus documentation built on April 8, 2022, 1:43 p.m.