scRNAseq-class {conclus} | R Documentation

## 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.

`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.

`clustersMarkers`

  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.
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.
getClustersMarkers(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
setClustersMarkers(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

[Package conclus version 1.0.0 Index]