Rphenograph             RphenoGraph clustering
add.10x.image           Add image data to iCellR object
add.adt                 Add CITE-seq antibody-derived tags (ADT)
add.vdj                 Add V(D)J recombination data
adt.rna.merge           Merge RNA and ADT data
bubble.gg.plot          Create bubble heatmaps for genes in clusters or
                        conditions.
capture.image.10x       Read 10X image data
cc                      Calculate Cell cycle phase prediction
cell.cycle              Cell cycle phase prediction
cell.filter             Filter cells
cell.gating             Cell gating
cell.type.pred          Create heatmaps or dot plots for genes in
                        clusters to find thier cell types using ImmGen
                        data.
change.clust            Change the cluster number or re-name them
clono.plot              Make 2D and 3D scatter plots for clonotypes.
clust.avg.exp           Create a data frame of mean expression of genes
                        per cluster
clust.cond.info         Calculate cluster and conditions frequencies
clust.ord               Sort and relabel the clusters randomly or based
                        on pseudotime
clust.rm                Remove the cells that are in a cluster
clust.stats.plot        Plotting tSNE, PCA, UMAP, Diffmap and other dim
                        reductions
cluster.plot            Plot nGenes, UMIs and perecent mito
data.aggregation        Merge multiple data frames and add the
                        condition names to their cell ids
data.scale              Scale data
down.sample             Down sample conditions
find.dim.genes          Find model genes from PCA data
findMarkers             Find marker genes for each cluster
find_neighbors          K Nearest Neighbour Search
g2m.phase               A dataset of G2 and M phase genes
gate.to.clust           Assign cluster number to cell ids
gene.plot               Make scatter, box and bar plots for genes
gene.stats              Make statistical information for each gene
                        across all the cells (SD, mean, expression,
                        etc.)
gg.cor                  Gene-gene correlation. This function helps to
                        visulaize and calculate gene-gene correlations.
heatmap.gg.plot         Create heatmaps for genes in clusters or
                        conditions.
hto.anno                Demultiplexing HTOs
i.score                 Cell cycle phase prediction
iba                     iCellR Batch Alignment (IBA)
iclust                  iCellR Clustering
load.h5                 Load h5 data as data.frame
load10x                 Load 10X data as data.frame
make.bed                Make BED Files
make.gene.model         Make a gene model for clustering
make.obj                Create an object of class iCellR.
myImp                   Impute data
norm.adt                Normalize ADT data. This function takes data
                        frame and Normalizes ADT data.
norm.data               Normalize data
opt.pcs.plot            Find optimal number of PCs for clustering
prep.vdj                Prepare VDJ data
pseudotime              Pseudotime
pseudotime.knetl        iCellR KNN Network
pseudotime.tree         Pseudotime Tree
qc.stats                Calculate the number of UMIs and genes per cell
                        and percentage of mitochondrial genes per cell
                        and cell cycle genes.
run.anchor              Run anchor alignment on the main data.
run.cca                 Run CCA on the main data
run.clustering          Clustering the data
run.diff.exp            Differential expression (DE) analysis
run.diffusion.map       Run diffusion map on PCA data (PHATE -
                        Potential of Heat-Diffusion for Affinity-Based
                        Transition Embedding)
run.impute              Impute the main data
run.knetl               iCellR KNN Network
run.mnn                 Run MNN alignment on the main data.
run.pc.tsne             Run tSNE on PCA Data. Barnes-Hut implementation
                        of t-Distributed Stochastic Neighbor Embedding
run.pca                 Run PCA on the main data
run.phenograph          Clustering the data
run.tsne                Run tSNE on the Main Data. Barnes-Hut
                        implementation of t-Distributed Stochastic
                        Neighbor Embedding
run.umap                Run UMAP on PCA Data (Computes a manifold
                        approximation and projection)
s.phase                 A dataset of S phase genes
spatial.plot            Plot nGenes, UMIs and perecent mito, genes,
                        clusters and more on spatial image
stats.plot              Plot nGenes, UMIs and percent mito
top.markers             Choose top marker genes
vdj.stats               VDJ stats
volcano.ma.plot         Create MA and Volcano plots.
