Man pages for shdam/cyCombine
Robust integration of single-cell cytometry datasets within and across technologies
| batch_correct | Run batch correction on data |
| compile_fcs | Compile all .fcs files in a directory to a flowset |
| compute_emd | Compute EMD |
| compute_mad | Compute MAD |
| convert_flowset | Convert a flowSet into a tibble |
| correct_data | Correct data using ComBat |
| correct_data_alt | Alternate correction |
| create_som | Create Self-Organizing Map |
| detect_batch_effect | Full function for detection of batch effects using cluster... |
| detect_batch_effect_express | Quicker function for detection of batch effects |
| df2SCE | Exporting a dataframe to SingleCellObject |
| evaluate_emd | Evaluate Earth Mover's Distance |
| evaluate_mad | Evaluate MAD |
| get_markers | Get markers from a dataframe |
| impute_across_panels | Impute non-overlapping channels for whole data sets |
| non_markers | Column names that are not cytometry markers |
| normalize | Batch-wise normalization of data |
| pipe | Pipe operator |
| plot_density | Density ridges for two sets |
| plot_dimred | Dimensionality reduction plot |
| plot_dimred_full | Dimensionality reduction plots - colored with labels, batches... |
| plot_save_four | Save four plots aligned with cowplot |
| plot_save_two | Save two plots aligned with cowplot |
| plot_umap_labels | Dimensionality reduction plots for a two-batch dataset before... |
| prepare_data | Prepare a directory of .fcs files |
| quantile_norm | Batch-wise quantile normalization per marker |
| run_analysis | Run analysis of a batch correction |
| salvage_problematic | Salvaging problematic channels - one at a time |
| transform_asinh | Transform data using asinh |
