| fit_models | R Documentation | 
This function fits a generalized linear model for each gene in a cell_data_set. Formulae can be provided to account for additional covariates (e.g. day collected, genotype of cells, media conditions, etc).
fit_models(
  cds,
  model_formula_str,
  expression_family = "quasipoisson",
  reduction_method = "UMAP",
  cores = 1,
  clean_model = TRUE,
  verbose = FALSE,
  ...
)
cds | 
 The cell_data_set upon which to perform this operation.  | 
model_formula_str | 
 A formula string specifying the model to fit for the genes.  | 
expression_family | 
 Specifies the family function used for expression responses. Can be one of "quasipoisson", "negbinomial", "poisson", "binomial", "gaussian", "zipoisson", "zinegbinomial", or "mixed-negbinomial". Default is "quasipoisson".  | 
reduction_method | 
 Which method to use with clusters() and partitions(). Default is "UMAP".  | 
cores | 
 The number of processor cores to use during fitting.  | 
clean_model | 
 Logical indicating whether to clean the model. Default is TRUE.  | 
verbose | 
 Logical indicating whether to emit progress messages.  | 
... | 
 Additional arguments passed to model fitting functions.  | 
a tibble where the rows are genes and columns are
 id character vector from rowData(cds)$id
 gene_short_names character vector from rowData(cds)$gene_short_names
 num_cells_expressed int vector from rowData(cds)$num_cells_expressed
gene_id character vector from row.names(rowData(cds))'
model GLM model list returned by speedglm
 model_summary model summary list returned by summary(model)
status character vector of model fitting status: OK when model converged, otherwise FAIL
  
    cell_metadata <- readRDS(system.file('extdata',
                                         'worm_embryo/worm_embryo_coldata.rds',
                                         package='monocle3'))
    gene_metadata <- readRDS(system.file('extdata',
                                         'worm_embryo/worm_embryo_rowdata.rds',
                                         package='monocle3'))
    expression_matrix <- readRDS(system.file('extdata',
                                             'worm_embryo/worm_embryo_expression_matrix.rds',
                                             package='monocle3'))
   
    cds <- new_cell_data_set(expression_data=expression_matrix,
                             cell_metadata=cell_metadata,
                             gene_metadata=gene_metadata)
    cds <- preprocess_cds(cds, num_dim=50)
    cds <- align_cds(cds, alignment_group = "batch",
                     residual_model_formula_str = "~ bg.300.loading + bg.400.loading +
                     bg.500.1.loading + bg.500.2.loading + bg.r17.loading + bg.b01.loading +
                     bg.b02.loading")
    cds <- reduce_dimension(cds)
    ciliated_genes <- c("che-1", "hlh-17", "nhr-6", "dmd-6", "ceh-36", "ham-1")
    cds_subset <- cds[rowData(cds)$gene_short_name %in% ciliated_genes,]
    gene_fits <- fit_models(cds_subset, model_formula_str = "~embryo.time")
  
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