cemitool: Full gene co-expression analysis
In CEMiTool: Co-expression Modules identification Tool

Description Usage Arguments Value Examples

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 = 1000,
  min_ngen = 30,
  diss_thresh = 0.8,
  plot = TRUE,
  plot_diagnostics = TRUE,
  order_by_class = TRUE,
  center_func = "mean",
  directed = FALSE,
  verbose = FALSE
)

`expr`	Gene expression `data.frame`.
`annot`	Sample annotation `data.frame`.
`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 `0.1`.
`apply_vst`	Logical. If TRUE, will apply Variance Stabilizing Transform before filtering genes. Currently ignored if parameter `filter` is FALSE.
`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 `"pearson"` or `"spearman"`. Default is `"pearson"`.
`cor_function`	A character string indicating the correlation function to be used. Supported functions are currently 'cor' and 'bicor'. Default is `"cor"`
`network_type`	A character string indicating if network type should be computed as `"signed"` or `"unsigned"`. Default is `"unsigned"`
`tom_type`	A character string indicating if the TOM type should be computed as `"signed"` or `"unsigned"`. Default is `"signed"`
`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 `TRUE`, merge similar modules.
`rank_method`	Character string indicating how to rank genes. Either "mean" (the default) or "median".
`ora_pval`	P-value for overrepresentation analysis. Default `0.05`.
`gsea_scale`	If TRUE, apply z-score transformation for GSEA analysis. Default is `TRUE`
`gsea_min_size`	Minimum size of gene sets for GSEA analysis. Default is `15`
`gsea_max_size`	Maximum size of gene sets for GSEA analysis. Default is `1000`
`min_ngen`	Minimal number of genes per submodule. Default `30`.
`diss_thresh`	Module merging correlation threshold for eigengene similarity. Default `0.8`.
`plot`	Logical. If `TRUE`, plots all figures.
`plot_diagnostics`	Logical. If `TRUE`, creates diagnostic plots. Overwritten if plot=FALSE.
`order_by_class`	Logical. If `TRUE`, samples in profile plot are ordered by the groups defined by the class_column slot in the sample annotation file. Ignored if there is no sample_annotation file. Default `TRUE`.
`center_func`	Character string indicating the centrality measure to show in the plot. Either 'mean' (the default) or 'median'.
`directed`	Logical. If `TRUE`, the igraph objects in interactions slot will be directed.
`verbose`	Logical. If `TRUE`, reports analysis steps.

Object of class CEMiTool

# 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)

## Not run: 
# 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)