Man pages for cellity
Quality Control for Single-Cell RNA-seq Data
| assess_cell_quality_PCA | ASSESS CELL QUALITY USING PCA AND OUTLIER DETECTION |
| assess_cell_quality_SVM | Assess quality of a cell - SVM version |
| cellity-package | Quality Control for Single-Cell RNA-seq Data |
| extract_features | Extracts biological and technical features for given dataset |
| extra_human_genes | Additional human genes that are used in feature extraction |
| extra_mouse_genes | Additional mouse genes that are used in feature extraction |
| feature_generation | Helper Function to create all features |
| feature_info | Information which genes and GO categories should be included... |
| mES1_features | Real test dataset containing all and common features from the... |
| mES1_labels | Real test dataset containing annotation of cells |
| multiplot | Internal multiplot function to combine plots onto a grid |
| normalise_by_factor | Internal function to normalize by library size |
| param_mES_all | Parameters used for SVM classification |
| param_mES_common | Parameters used for SVM classification |
| plot_pca | Plots PCA of all features. Colors high and low quality cells... |
| sample_counts | Sample gene expression data containing 40 cells |
| sample_stats | Sample read statistics data containing 40 cells |
| simple_cap | Converts all first letters to capital letters |
| sum_prop | Sums up normalised values of genes to groups. |
| training_mES_features | Original training dataset containing all and common features... |
| training_mES_labels | Original training dataset containing annotation of cells |
| uni.plot | Internal function to detect outliers from the mvoultier... |
