Man pages for SignacX
Cell Type Identification and Discovery from Single Cell Gene Expression Data
| CID.entropy | Normalized Shannon entropy-based "unclassified" assignment |
| CID.GetDistMat | Computes distance matrix from edge list |
| CID.IsUnique | Extracts unique elements |
| CID.LoadData | Load data file from directory |
| CID.LoadEdges | Load edges from edge list for single cell network |
| CID.Louvain | Detects community substructure by Louvain community detection |
| CID.Normalize | Library size normalize |
| CID.smooth | Smoothing function |
| CID.writeJSON | Writes JSON file for SPRING integration |
| GenerateLabels | Generates cellular phenotype labels |
| Genes_Of_Interest | Genes of interest for drug discovery / disease biology... |
| get_colors | Get HEX colors |
| GetModels_HPCA | Loads neural network models from GitHub |
| GetTrainingData_HPCA | Loads bootstrapped HPCA training data from GitHub |
| KSoftImpute | KNN-based imputation |
| MASC | Mixed effect modeling |
| ModelGenerator | Generates an ensemble of neural network models. |
| SaveCountsToH5 | Save count_matrix.h5 files for SPRING integration |
| Signac | Classification of cellular phenotypes in single cell data |
| SignacBoot | Generates bootstrapped single cell data |
| SignacFast | Fast classification of cellular phenotypes |
