Mixed effect modeling
MASC was imported from https://github.com/immunogenomics/masc.
Performs mixed-effect modeling.
MASC( dataset, cluster, contrast, random_effects = NULL, fixed_effects = NULL, verbose = FALSE )
dataset |
data frame of covariate, cell type, clustering or disease information |
cluster |
celltypes returned by Signac or cluster identities |
contrast |
Typically disease |
random_effects |
User specified random effect variables in dataset |
fixed_effects |
User specific fixed effects in dataset |
verbose |
If TRUE, algorithm reports outputs |
mixed effect model results
## Not run: # Load metadata file.dir = "https://kleintools.hms.harvard.edu/tools/client_datasets/" file = "AMP_Phase1_SLE_Apr2019/FullDataset_v1/categorical_coloring_data.json" download.file(paste0(file.dir, file, "?raw=true"), destfile = "categorical_coloring_data.json") d = rjson::fromJSON(file='categorical_coloring_data.json') d = data.frame(sapply(d, function(x) x$label_list)) # run MASC x = json_data$CellStates # optionally use clusters or cell types Q = MASC(d, cluster = x, contrast = 'Disease', random_effects = c( "Tissue", "Plate", "Sample")) ## End(Not run)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.