DNBcompute: DNBcompute

In Kaiyu-W/DNBr: Compute the Dynamic Network Biomarkers (DNB) model

DNBcompute

Description

Compute the Dynamic Network Biomarkers(DNB) model

Usage

DNBcompute(
  data,
  meta,
  diffgenes = NULL,
  allgenes = NULL,
  meta_levels = NULL,
  high_method = c("high_cv", "top_gene"),
  high_cutoff = 0.6,
  cutree_method = c("h", "k"),
  cutree_cutoff = 0.98,
  minModule = 7,
  maxModule = 60,
  quiet = FALSE,
  fastMode = FALSE,
  writefile = FALSE,
  cluster_fun = NULL,
  cluster_args = NULL,
  size_effect = TRUE
)

Arguments

data	the gene expression matrix, which can be a single-cell RNA-seq GEM with at least three group/clusters or a matrix merging bulk GEMs from at least three different sample
meta	a data.frame with rownames as cell-id as well as one column of group infomation
diffgenes	which genes we're interested in, or no special ones (all, default)
allgenes	the whole genes that ordered in advance by expression, or the rownames of GEM (default)
meta_levels	the order of meta group, default ordered by decreasing if NULL
high_method	the method to select genes for the first step, by either high_cv (default) or top_gene
high_cutoff	the cutoff value corresponding to the high_method, with the range between 0 - 1(all) for high_cv and 1 - #allgenes(all) for top_gene or not to select highly variable genes but use all genes when -1
cutree_method	the method to select numbers of tree (module) from hclust, by either h (height, default) or k (number K)
cutree_cutoff	the cutoff value corresponding to the cutree_method, with the range between 0-1 for h and a number greater than 0 for k
minModule	the min number of genes of the module meeting requirements
maxModule	the max number of genes of the module meeting requirements
quiet	do not print output of process during calculation (against verbose), default FALSE
fastMode	avoid using for loop, rathan apply-like function, default FALSE; if TRUE, quiet will be set as TRUE
writefile	write results of each group into DNB_Module_information_xx.txt with tab delimiter, default FALSE
cluster_fun	customized function that user design for clustering to find module, default NULL (hierarchical by stats::hclust(d, method = "complete", members = NULL)) This function should do function of clustering (e.g hclust + cutree), with input that first arg "d" = distance matrix and output "named int vector". If assigned, cutree_method and cutree_cutoff would be ignored
cluster_args	a list of extra arguments to the cluster_fun call. The names attribute of args gives the argument names. (same to base::do.call(args))
size_effect	whether consider the effect of sample size when compute CI of DNB, default TRUE

Details

return a S3 object includes several S4 objects

(optional) write score results into DNB_score_matrix.txt

Value

S3:DNB_output

Author(s)

Kaiyu Wang, in ChenLab of CAS, Shanghai, China

Examples

data(data.example)
data(meta.example)
a <- DNBcompute(data.example, meta.example)
a

Kaiyu-W/DNBr documentation built on April 27, 2024, 10:09 a.m.