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Norm count matrix (n_genes X n_cells).

K-nearest neighbors matrix (n_cells X n_cells).

Vector of genes for which the functionCIARA_geneis run.

Integer.Number of cores to use.

p value returned by the functionfisher.test withparameter alternative = "g"

odds_ratio returned by the functionfisher.testwith parameter alternative = "g"

Integer. Minimum number of local regions (cell with itsknn neighbours) where the binarized gene expression is enriched in 1.

Logical.For a given gene, the fisher test is run in thelocal regions of only the cells where the binarized gene expression is 1.

Norm count matrix (n_genes X n_cells).

K-nearest neighbors matrix (n_cells X n_cells).

numeric vector with the gene expression (length equalto n_cells). The gene expression is binarized (equal to 0/1 in the cellswhere the value is below/above the median)

p value returned by the functionfisher.test withparameter alternative = "g"

odds_ratio returned by the functionfisher.testwith parameter alternative = "g"

Integer. Minimum number of local regions (cell with itsknn neighbours) where the binarized gene expression is enriched in 1.

Logical.For a given gene, the fisher test is run in thelocal regions of only the cells where the binarized gene expression is 1.

Raw count matrix (n_genes X n_cells).

Character name of the Seurat project.

Numeric value specifying the parameterresolutionused in the Seurat functionFindClusters.

Numeric value specifying the parameterk.param inthe Seurat functionFindNeighbors

Numeric value specifying the maximum number of the PCAdimensions used in the parameterdims for the Seurat functionFindNeighbors

vector of features specifying the argumentfeatures in the Seurat functionRunPCA.

Raw count matrix (n_genes X n_cells).

Numeric value specifying the parameterresolutionused in the Seurat functionFindClusters.

Numeric value specifying the parameterk.param inthe Seurat functionFindNeighbors

Numeric value specifying the maximum number of the PCAdimensions used in the parameterdims for the Seurat functionFindNeighbors

Character.Name of the original cluster for which the subclustering is done.

Seurat object as returned bycluster_analysis_integrate_rare

vector with all values of resolution for which theSeurat functionFindClusters is run

Norm count matrix (n_genes X n_cells).

threshold in expression for a given gene

minimum number of cells where a gene is expressed at alevel above threshold

maximum number of cells where a gene is expressed at alevel above threshold

Seurat object as returned bycluster_analysis_sub or bycluster_analysis_integrate_rare.

Vector of length equal to the number of cells, with clusterassignment.

Vector of length equal to the number of cells, with cellnames.

Integer. Number of top marker genes to keep for eachcluster.

original cluster assignment that need to be updated

new cluster assignment that need to be integrated withold_cluster.

Threshold in size for clusters innew_cluster. Onlycluster with number of cells smaller thanmax_number will beintegrated inold cluster. Ifmax_number is NULL, then all the clusters innew_cluster are integrated inold cluster.

Norm count matrix (genes X cells).

Vector of length equal to the number of cells, with clusterassignment.

Third element of the output list asreturned by the functionmarkers_cluster_seurat

Integer. Maximum number of markers for each cluster forwhich we want to plot the expression.

Integer. Size of the dots to be plotted.

Size of the text in the heatmap plot.

Norm count matrix (genes X cells).

Data frame with dimensionality reduction coordinates.Number of rows must be equal to the number of cells

Character name of the gene.

Character name.

Data frame with dimensionality reduction coordinates.Number of rows must be equal to the number of cells

Norm count matrix (genes X cells).

Vector with gene names for which we want to visualizethe sum in each cell.

Character value.

First element returned bymarkers_cluster_seurat

Second element returned bymarkers_cluster_seurat

Vector of length equal to the number of cells, with clusterassignment.

Vector or length equal to the number of cells, specifyingthe condition of the cells (i.e. batch, dataset of origin..)

Norm count matrix (genes X cells).

Size of the text in the heatmap plot.

Data frame with dimensionality reduction coordinates.Number of rows must be equal to the number of cells

vector of length equal to n_rows in coordinate_umap.Each cellwill be coloured following a gradient according to the corresponding valueof this vector.

Character vector specifying the highly localized genes in eachcell. It is the output fromselection_localized_genes.

Set the min limit on the x axis.

Set the max limit on the x axis.

Set the min limit on the y axis.

Set the min limit on the y axis.

Data frame with dimensionality reduction coordinates.Number of rows must be equal to the number of cells

Vector of length equal to the number of cells, with clusterassignment.

Norm count matrix (genes X cells).

vector of highly localized genes as provided by thelast element of the list given as output fromCIARA_mixing_final.

Minimum number of cells where a genes must beexpressed (> 0).

Maximum number of genes to show for each cell in theinteractive plot fromplot_interactive.

Raw count matrix (n_genes X n_cells).

Vector of length equal to the number of cells, with clusterassignment.

Character vector with localized genes detected by CIARA.

Character vector with all the genes names to use asbackground for the Fisher test.

Integer value. Number of top HVGs provided by the SeuratfunctionFindVariableFeatures.

Threshold on p values provided by Fisher test.

The first one is alist with length equal to the number of clusters. Each entry is list ofthree elements. The first two elements contain the p value and the oddsration given by the Fisher test The third is a vector with genes names thatare present both inlocalized_genes and in topnumber_hvg HVGs.

a character vector with the name of the cluster thathave a p value smaller thanmin_p_value.

Vector of length equal to the number of cells, with clusterassignment.

Character. Label of one specify cluster

Norm count matrix (genes X cells).

Third element of the output list as returned by thefunctionmarkers_cluster_seurat

Numeric. The median of the genes across cells belong tosingle_cluster has to be greater thanthreshold in order to beconsider as a white-black marker forsingle_cluster