# load required libraries
library(tidyverse)
library(WGCNA)
library(xtable)
# load data
load('data/rkip_wgcna.rda')
# global variables
tables_dir <- 'manuscript/tables/'
# generate table
df <- exportNetworkToVisANT(net$adj, threshold = .1)
string <- read_tsv('data/string_interactions.tsv')
full_join(df, string) %>%
filter(from == 'PEBP1') %>%
left_join(select(ann, symbol, category), by = c('to'='symbol')) %>%
mutate(evidence = ifelse(is.na(evidence), 'novel', evidence)) %>%
filter(evidence != 'combined_score') %>%
mutate(evidence = str_split(evidence, '_', simplify = TRUE)[, 1]) %>%
group_by(category, evidence) %>%
summarise(gene = paste(unique(to), collapse = ', ')) %>%
ungroup() %>%
mutate(category = case_when(category == 'autophagy' ~ 'Autophagy',
category == 'emt' ~ 'EMT',
category == 'pebp' ~ 'PEB')) %>%
mutate(category = ifelse(duplicated(category), '', category)) %>%
setNames(c('Category', 'Evidence', 'Gene')) %>%
xtable(caption = 'Summary of previously reported and novel PEBP1 interactions.',
align = 'clll',
label = 'tab:previousley_reported') %>%
print(include.rownames = FALSE,
booktabs = TRUE,
caption.placement = 'top',
table.placement = 'H',
sanitize.text.function = identity,
comment = FALSE,
file = paste(tables_dir, 'previously_reported.tex', sep = '/'))
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