BinaryPCA               Performs Binary PCA (as outlined in our paper).
                        This function take the input of gene expression
                        profile and perform PCA on gene detection
                        pattern
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 in toy dataset
diagnose                Perform diagnoisis of dispersion on the
                        expression profile to check whether scBFA works
                        on specific dataset
disperPlot              Reference dataset(disperPlot)
exprdata                scRNA-seq dataset(exprdata)
getGeneExpr             Function to extract gene expression matrix from
                        input observation matrix
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 calls to the optim()
                        function.
gradient_chunk          Calculate gradient of the negative log
                        likelihood, used for calls to the optim()
                        function.
scBFA                   Perform BFA model on the expression profile
scNoiseSim              simulation to generate scRNA-seq data with
                        varying level of gene detection noise versus
                        gene count noise
zinb_toy                example zinb object after fitting a toy dataset
                        with 5 cells and 10 genes
