#-------------------------------------------------------------------------------
# Function: hypergeometric test
#-------------------------------------------------------------------------------
hypergeo <- function(white.drawn, white, black, drawn, do.log=FALSE) {
  # Info: http://digitheadslabnotebook.blogspot.com/2011/02/using-r-for-introductory-statistics_21.html
  # dhyper(q, m, n, k, log = FALSE)
  #        q = number of successes; "white balls drawn" (here: number of genes that overlap)
  #        m + n = N ; N = total number of genes
  #        m = "white balls in urn"; total number of TF-bound genes
  #        n = "black balls in urn"; total number of genes NOT bound by the TF
  #        k = "number of balls drawn from urn"; sample size
  if (white < 1) {return(NA)}
  p <- phyper(white.drawn-1, white, black, drawn, lower.tail = FALSE, log.p=do.log)
  return(p)
} # end: hypergeo

#-------------------------------------------------------------------------------
# Set the working directory and load the data files
#-------------------------------------------------------------------------------
setwd("~/Desktop/R_Project/Gene_overlap")
getwd()
files <- list.files(pattern="*.txt", full.names = TRUE)
files

data.list <- lapply(files, function(fil) {
  scan(file=fil, what=character())
})

names(data.list) <- basename(files) %>% stringr::str_remove("\.txt$")

str(data.list)
# List of 8
# $ GSE108363_BCGdown_D:chr [1:350] "IL1B" "IL6" "IL1A" "CCL20" ...
# $ GSE108363_BCGdown_V: chr [1:267] "IL6" "CCL20" "IL1A" "CXCL5" ...
# $ GSE108363_BCGup_D  : chr [1:250] "FABP4" "CMTM2" "FUCA1" "CD36" ...
# $ GSE108363_BCGup_V  : chr [1:429] "FCN1" "FCGR3B" "MNDA" "CPVL" ...
# $ GSE108363_MTBdown_D: chr [1:86] "CCL20" "IL1B" "IL1A" "IL6" ...
# $ GSE108363_MTBdown_V: chr [1:244] "IL1B" "IL1A" "CCL20" "IL6" ...
# $ GSE108363_MTBup_D  : chr [1:128] "FUCA1" "FGL2" "TGFBI" "CPVL" ...
# $ GSE108363_MTBup_V  : chr [1:286] "FABP4" "RNASE1" "MNDA" "CPVL" ...

intersect(data.list$GSE108363_BCGdown_D, data.list$GSE108363_BCGdown_V) %>% length

sapply(data.list, length)



#-------------------------------------------------------------------------------
# Using the intersect function to see the overlaps
#-------------------------------------------------------------------------------

data.file1 <- "GSE108363_BCGdown_V.txt"
data.file2 <- "GSE108363_BCGdown_D.txt"
data.file3 <- "GSE108363_BCGup_V.txt"
data.file4 <- "GSE108363_BCGup_D.txt"
data.file5 <- "GSE108363_MTBdown_V.txt"
data.file6 <- "GSE108363_MTBdown_D.txt"
data.file7 <- "GSE108363_MTBup_V.txt"
data.file8 <- "GSE108363_MTBup_D.txt"

genevect1 <- scan(data.file1, what=character(), sep="n")
genevect2 <- scan(data.file2, what=character(), sep="n")
genevect3 <- scan(data.file3, what=character(), sep="n")
genevect4 <- scan(data.file4, what=character(), sep="n")
genevect5 <- scan(data.file5, what=character(), sep="n")
genevect6 <- scan(data.file6, what=character(), sep="n")
genevect7 <- scan(data.file7, what=character(), sep="n")
genevect8 <- scan(data.file8, what=character(), sep="n")


filelist <- list(data.file1, data.file2, data.file3, data.file4, data.file5, data.file6, data.file7, data.file8)
all(sapply(filelist, file.exists))


#-------------------------------------------------------------------------------
# read files:
#-------------------------------------------------------------------------------

gene.lists <- lapply(filelist, function(f) {
  scan(file=f, what=character())
})


#-------------------------------------------------------------------------------
# set up empty matrix
#-------------------------------------------------------------------------------
x <- (length(gene.lists))^2
x
y <- rep(NA, x)
mx <- matrix(y, ncol=length(gene.lists))
mx
row.names(mx) <- sapply(filelist, basename) %>% stringr::str_remove('.txt$')
colnames(mx) <- sapply(filelist, basename) %>% stringr::str_remove('.txt$')
mx

mx.overlap.count <- mx

    #-------------------------------------------------------------------------------
    # seq_along(gene.lists) # 1 2 3 4 5 6 7 8
    #-------------------------------------------------------------------------------
    for (i in seq_along(gene.lists)) {
      g1 <- gene.lists[[i]]
      for (j in seq_along(gene.lists)) {
        g2 <- gene.lists[[j]]
        a <- intersect(g1, g2)
        b <- length(a)
        mx.overlap.count[j,i] <- b
      }
    }

    mx.overlap.count
    View(mx.overlap.count)

    #-------------------------------------------------------------------------------
    # looking at gene overlaps in terms of %
    #-------------------------------------------------------------------------------
    # modify the code written above by adding the following to the innermost loop:
    # get max of g1 and g2
    # divide overlap by the max
    # calculate the %

    # seq_along(gene.lists) # 1 2 3 4 5 6 7 8
    mx.overlap <- mx
    for (i in seq_along(gene.lists)) {
      g1 <- gene.lists[[i]]
      for (j in seq_along(gene.lists)) {
        g2 <- gene.lists[[j]]
        a <- intersect(g1, g2)
        b <- length(a)
        maxN = max(length(g1), length(g2))
        mx.overlap[j,i]= 100* b / maxN
        mx.overlap.count[j,i] <- b
      }
    }

    mx.overlap
    View(mx.overlap)