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| 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 |
| 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 |
| demo.obj | An object of class iCellR for demo |
| 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 |
| iba | iCellR Batch Alignment (IBA) |
| iclust | iCellR Clustering |
| load.h5 | Load h5 data as data.frame |
| load10x | Load 10X data as data.frame |
| 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. |
| Rphenograph | RphenoGraph clustering |
| 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 |
| 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. |