Man pages for quon-titative-biology/bfa
A dimensionality reduction tool using gene detection pattern to mitigate noisy expression profile of scRNA-seq
| BinaryPCA | Performs Binary PCA (as outlined in our paper). This function... |
| celltype | Cell types as labels of example scRNA-seq dataset(exprdata) |
| celltype_toy | toy cell type vector with 3 cell types generated for 5 cells... |
| diagnose | Perform diagnoisis of dispersion on the expression profile to... |
| disperPlot | Reference dataset(disperPlot) |
| exprdata | scRNA-seq dataset(exprdata) |
| getGeneExpr | Function to extract gene expression matrix from input... |
| getLoading | Function to get low dimensional loading matrix |
| getScore | Function to get low dimensional embedding matrix |
| gradient | Calculate gradient of the negative log likelihood, used for... |
| gradient_chunk | Calculate gradient of the negative log likelihood, used for... |
| InitBinaryFA | This function should be called to initialize input parameters... |
| neg_loglikelihood | Calculate negative penalized likelihood, used for calls to... |
| neg_loglikelihood_chunk | Calculate negative penalized likelihood, used for calls to... |
| OptimBFA | Optimize parameters of BFA's likelihood function |
| restore | Restore the vector of parameter space into their seperated... |
| scbfa | Perform BFA model on the expression profile |
| scNoiseSim | simulation to generate scRNA-seq data with varying level of... |
| zinb_toy | example zinb object after fitting a toy dataset with 5 cells... |
