Plot individual eigengene distributions

Usage

plot_consensus_eig_dist(
  eigen_list,
  target_study_index = 1,
  filename = NA,
  device = "png",
  width = 12,
  height = 10,
  dpi = 1000
)

Arguments

eigen_list: a list of community signatures (eigengenes) for studies, using the output of calc_consensus_memberships() as the membership_matrix.
target_study_index: the study you want to normalized eigengenes to for displaying the distributions. It should likely be the largest/best quality study
filename: File name
device: Device to use. Can either be a device function (e.g. png), or one of "eps", "ps", "tex" (pictex), "pdf", "jpeg", "tiff", "png", "bmp", "svg" or "wmf" (windows only).
width: Plot width in units ("in", "cm", "mm", or "px"). If not supplied, uses the size of current graphics device.
height: Plot height in units ("in", "cm", "mm", or "px"). If not supplied, uses the size of current graphics device.
dpi: Plot resolution. Also accepts a string input: "retina" (320), "print" (300), or "screen" (72). Applies only to raster output types.

Value

eigengene distributions if filename is na, and saved figure is filename provided

Details

In icWGCNA eigen_list is created using icWGCNA::compute_eigengene_matrix() for each study and then combining all outputs into a list.

Examples

if (FALSE) {
memb_list <- list(
  GSE39582 = GSE39582_icwgcna$community_membership,
  READ = read_icwgcna$community_membership,
  COAD = coad_icwgcna$community_membership
)
ma <- construct_rbh_correlation_based(
  memb_list,
  upper_quant = .99,
  lower_quant = .05,
  max_rank = 2
)
consensus_comms <- detect_consensus_communities(ma)
consensus_memb <- calc_consensus_memberships(consensus_comms, memb_list,
  gene_cohort_N = 2
)

# Need to use icWGCNA for individual eigengenes
GSE39582_eigen <- icWGCNA::compute_eigengene_matrix(
  ex = GSE39582_df,
  membership_matrix = consensus_memb
)
read_eigen <- icWGCNA::compute_eigengene_matrix(
  ex = read_df,
  membership_matrix = consensus_memb
)
coad_eigen <- icWGCNA::compute_eigengene_matrix(
  ex = coad_df,
  membership_matrix = consensus_memb
)
eigen_list <- list(GSE39582_eigen, read_eigen, coad_eigen)

plot_consensus_eig_dist(eigen_list)
}