cemitool {CEMiTool} | R Documentation |
Defines co-expression modules and runs several different analyses.
cemitool(expr, annot, gmt, interactions, filter = TRUE, filter_pval = 0.1, apply_vst = FALSE, n_genes, eps = 0.1, cor_method = c("pearson", "spearman"), cor_function = "cor", network_type = "unsigned", tom_type = "signed", set_beta = NULL, force_beta = FALSE, sample_name_column = "SampleName", class_column = "Class", merge_similar = TRUE, rank_method = "mean", ora_pval = 0.05, gsea_scale = TRUE, gsea_min_size = 15, gsea_max_size = 500, min_ngen = 30, diss_thresh = 0.8, plot = TRUE, order_by_class = TRUE, center_func = "mean", directed = FALSE, verbose = FALSE)
expr |
Gene expression |
annot |
Sample annotation |
gmt |
A data.frame containing two columns, one with pathways and one with genes |
interactions |
A data.frame containing two columns with gene names. |
filter |
Logical. If TRUE, will filter expression data. |
filter_pval |
P-value threshold for filtering.Default |
apply_vst |
Logical. If TRUE, will apply Variance Stabilizing Transform before filtering genes.
Currently ignored if parameter |
n_genes |
Number of genes left after filtering. |
eps |
A value for accepted R-squared interval between subsequent beta values. Default is 0.1. |
cor_method |
A character string indicating which correlation coefficient is
to be computed. One of |
cor_function |
A character string indicating the correlation function to be used. Supported functions are
currently 'cor' and 'bicor'. Default is |
network_type |
A character string indicating if network type should be computed
as |
tom_type |
A character string indicating if the TOM type should be computed
as |
set_beta |
A value to override the automatically selected beta value. Default is NULL. |
force_beta |
Whether or not to automatically force a beta value based on number of samples. Default is FALSE. |
sample_name_column |
A character string indicating the sample column name of the annotation table. |
class_column |
A character string indicating the class column name of the annotation table. |
merge_similar |
Logical. If |
rank_method |
Character string indicating how to rank genes. Either "mean" (the default) or "median". |
ora_pval |
P-value for overrepresentation analysis. Default |
gsea_scale |
If TRUE, apply z-score transformation for GSEA analysis. Default is |
gsea_min_size |
Minimum size of gene sets for GSEA analysis. Default is |
gsea_max_size |
Maximum size of gene sets for GSEA analysis. Default is |
min_ngen |
Minimal number of genes per submodule. Default |
diss_thresh |
Module merging correlation threshold for eigengene similarity.
Default |
plot |
Logical. If |
order_by_class |
Logical. If |
center_func |
Character string indicating the centrality measure to show in the plot. Either 'mean' (the default) or 'median'. |
directed |
Logical. If |
verbose |
Logical. If |
Object of class CEMiTool
## Not run: # Get example expression data data(expr0) # Run CEMiTool analyses cem <- cemitool(expr=expr0) # Run CEMiTool applying Variance Stabilizing Transformation to data cem <- cemitool(expr=expr0, apply_vst=TRUE) # Run CEMiTool with additional processing messages cem <- cemitool(expr=expr0, verbose=TRUE) # Run full CEMiTool analysis ## Get example sample annotation data data(sample_annot) ## Read example pathways file gmt_fname <- system.file("extdata", "pathways.gmt", package = "CEMiTool") gmt_in <- read_gmt(gmt_fname) ## Get example interactions file int_df <- read.delim(system.file("extdata", "interactions.tsv", package = "CEMiTool")) ## Run CEMiTool cem <- cemitool(expr=expr0, annot=sample_annot, gmt=gmt_in, interactions=int_df, verbose=TRUE, plot=TRUE) # Create report as html file generate_report(cem, directory = "./Report", output_format="html_document") # Write analysis results into files write_files(cem, directory="./Tables", force=TRUE) # Save all plots save_plots(cem, "all", directory="./Plots") ## End(Not run)