yeast DIP analysis

using the 2017 data sets.  Median interactions per gene: 4, average is 8.8 for all genes.

list.files()

## [1] "_explore_dip.html"  "_explore_dip.Rmd"   "Scere20170205.csv" 
## [4] "Scere20170205.txt"  "Scere20170205.xlsx"

#library(xlsx)
tb = read.table("Scere20170205.txt", header=T, sep="\t", row.names=NULL)
#tb = read.xlsx("Scere20170205.xlsx", 1)

Visual check show that there are interactions between yeast proteins and non-yeast proteins (such as human and flys) Some the column names are move by one-column.

big2small = function(char1, char2) {
  if ( char1 > char2) {
    return( c( char1, char2) )
  } else {
    return( c(char2, char1) )
  }
}

for( i in 1:length(tb[,1])) {
#for( i in 1:19) {
  pair = big2small(as.character(tb[i, 1]), as.character(tb[i, 2]))
  tb$pairID[i] = paste( pair[1], pair[2], sep = "::")
}

How many ExE interactions?

unique_EEpairs = unique(tb$pairID)
all_names = c();
for( pair in unique_EEpairs) {
  all_names = c(all_names, unlist( strsplit(pair, split="::") ))
  
}

degree = table(all_names)
str(degree)

##  'table' int [1:5176(1d)] 3 68 7 6 9 9 56 5 5 1 ...
##  - attr(*, "dimnames")=List of 1
##   ..$ all_names: chr [1:5176] "DIP-1000N|refseq:NP_014991|uniprotkb:P12689" "DIP-1001N|refseq:NP_010241|uniprotkb:Q07350" "DIP-1002N|refseq:NP_010206|uniprotkb:Q07468" "DIP-1003N|refseq:NP_010131|uniprotkb:P25441" ...

mean(degree)

## [1] 8.878284

median(degree)

## [1] 4