Package index • TS

All functions

as.factor(): Human IGHD families in ascending numeric order
as.factor(): Human IGHD genes according to their relative locus location
as.factor(): Human IGHJ genes according to their relative locus location
as.factor(): Human IGHV families in ascending numeric order
as.factor(): Human IGHV families in ascending numeric order with IGHV6 and 7 grouped
as.factor(): Human IGHV genes according to their relative locus location
as.factor(): Human IGKJ genes according to their relative locus location
as.factor(): Human IGKV families in ascending numeric order
as.factor(): Human IGKV genes according to their relative locus location
as.factor(): Human IGLC genes according to their relative locus location
as.factor(): Human IGLJ genes according to their relative locus location
as.factor(): Human IGLV families in ascending numeric order
as.factor(): Human IGLV genes according to their relative locus location
TS_DEenrichRPlot(): A wrapper around the DEnrichRPlot from the 'Seurat' package
TS_FindConservedMarkers(): Find conserved markers within two groups
TS_Find_DEGs_and_overlap(): Find the upregulated DEGs for each cluster, comparing two clusters. As well as the conserved markers between them.
TS_IGHV_usage_prop_with_stats(): Plots IGHV usage between two groups using Fisher's Exact Test
TS_Seurat_from_file(): Process CellRanger output files with Seurat
TS_add_sig_segments_and_labels(): Adds test results to column charts
TS_calculate_ratios(): Calculate light chain ratios of a Seurat object, requires light chain data in metadata "light.chain"
TS_cellnumbers_per_PC_and_resolution(): Calculate cellnumbers per cluster for each combination of 'number or PCs' and 'resolution'
TS_compare_PC_and_resolution(): Compare number of clusters for combinations of number of PCs and resolution
TS_compute_pairwise_fisher(): Compute pairwise Fisher tests for gene usage
TS_count_VDJ(): Not sure if this function is desirable anymore. So use it at your own risk
TS_count_VDJ_7.0(): Count VDJ from Cellranger 7.0
TS_dataframe_to_fasta(): Converts a dataframe and saves it in Fasta format
TS_export_cluster_ids(): Export cell barcodes for each cluster
TS_export_named_ids(): Export identities for each cluster, which are not numerical
TS_extract_ig_mean_median_rank_per_PC(): Extract the mean and median values of Ig-genes from a list of PCA feature loadings
TS_extract_ig_ranks_per_PC(): Extract the 'rank' for each of the Ig-genes
TS_extract_ranked_genes_per_PC(): Extract an ordered list of feature importance for each of the first 50 principal components
TS_featureplot_to_pdf(): Export featureplot as pdf to your working directory
TS_featureplot_to_pdf_A4(): Export featureplot to pdf in A4 format
TS_featureplot_to_pdf_no_leg_no_axes(): Export featureplot to pdf without legend and axes
TS_featureplots(): Output one or multiple featureplots
TS_filter_marker_list(): Filter list of markers from FindMarkers function, needs to be output into new df
TS_format_IMGT_to_cellranger(): Convert IMGT VDJ data to Cell Ranger–like format
TS_plot_3D(): Plot your Seurat object in 3D.
TS_plot_IG_usage(): Plots Ig usage between two groups using Fisher's Exact Test
TS_plot_IG_usage_legacy(): Plots Ig usage between two groups using Fisher's Exact Test
TS_plot_column_chart(): Create column chart with ggplot2
TS_plot_column_pattern_chart(): Create column chart with pattern with ggplot2
TS_plot_counts_boxplot(): Plot counts for a gene in a Seurat object as boxplot
TS_plot_counts_violin(): Plot counts for a gene in a Seurat object as violinplot
TS_plot_enrichR(): Plot the output from TS_run_enrichR
TS_project_scRNAseq_dataset(): Projects one Seurat object onto another
TS_project_scRNAseq_dataset_export_query(): Projects one Seurat object onto another and exports resulting dataframe
TS_run_enrichR(): Wrapper around the enrichR package.
TS_seurat_object_stats(): Prints stats about your Seurat object
TS_svg_from_featureplot(): Export featureplot as svg to your working directory
TS_svg_from_plot(): Export any plot as svg
TS_visdimloadings(): Plot gene contribution to each principal component
ram_usage(): RAM usage of objects.