Functional annotation summary for WGCNA modules

Implementation

Script: 19-annotate-wgcna-modules.py joins wgcna_ortholog_module_assignments.csv with ortholog_groups_annotated.csv on group_id (OG_xxxxx)
Summarization: Counts and ranks GO terms (BP/CC/MF), GO Slim pathways, and protein functions per module
Output: 7 files in M-multi-species/output/18-ortholog-wgcna/:
- wgcna_module_annotation_summary.txt - detailed report with top 10 terms per category for all 15 modules
- wgcna_module_overview.csv - per-module statistics (size, coverage, dominant terms)
- 5 CSV matrices showing term distributions across modules (GO BP/CC/MF, GO Slim, proteins)

All output:https://github.com/urol-e5/timeseries_molecular/tree/main/M-multi-species/output/18-ortholog-wgcna

url <- "https://raw.githubusercontent.com/urol-e5/timeseries_molecular/refs/heads/main/M-multi-species/output/18-ortholog-wgcna/wgcna_module_go_bp_summary.csv"
df <- read.csv(url, stringsAsFactors = FALSE, check.names = FALSE)
head(df)

                                                                    term
1 positive regulation of transcription by RNA polymerase II [GO:0045944]
2 negative regulation of transcription by RNA polymerase II [GO:0000122]
3          regulation of transcription by RNA polymerase II [GO:0006357]
4        positive regulation of DNA-templated transcription [GO:0045893]
5                                               proteolysis [GO:0006508]
6                                         protein transport [GO:0015031]
  module_0 module_1 module_2 module_3 module_4 module_5 module_6 module_7
1       14       33       40       16       21       35        9       13
2       16       36       25       16       17       23       15       13
3       22       28       28       18       14       27        0        0
4       14       26       29       14        0       22        0        0
5        0       35       19       20       15        0        0       16
6        9       33        0       21        0       17       12       12
  module_8 module_9 module_10 module_11 module_12 module_13 module_14 total
1        8        4         0         0         3         0         4   200
2        7        0         0         0         3         0         2   173
3        0        0         3         0         0         0         3   143
4        5        0         0         0         3         0         0   113
5        0        0         2         0         0         3         0   110
6        0        0         0         0         0         0         0   104

library(DT)

datatable(
  df,
  options = list(
    pageLength = 10,
    autoWidth = TRUE
  ),
  filter = 'top',      # column filters at the top
  rownames = FALSE
)