BIOGRID yeast PPI analysis
H Qin
11/16-27/2017
rm(list=ls());
datapath = "~/data/biogrid/";
list.files(path=datapath, pattern = "csv")## [1] "yeast-biogrid-smalltest.csv" "yeast-biogrid.csv"debug = 1; #tb = read.csv(paste(datapath, "yeast-biogrid-smalltest.csv", sep=''))
tb = read.csv(paste(datapath, "yeast-biogrid.csv", sep=''))
tb$Systematic.Name.Interactor.A = as.character( tb$Systematic.Name.Interactor.A )
tb$Systematic.Name.Interactor.B = as.character( tb$Systematic.Name.Interactor.B )tb.ppi = tb[ tb$Experimental.System.Type =='physical', ] #142657 rows
tb.ppi = tb.ppi[ !is.na(tb.ppi$Systematic.Name.Interactor.A), ]#141962 rows
tb.ppi = tb.ppi[ !is.na(tb.ppi$Systematic.Name.Interactor.B), ]#141640 rows
#tb.ppi$Synonyms.Interactor.A = as.character( tb.ppi$Synonyms.Interactor.A )
#tb.ppi$Synonyms.Interactor.B = as.character( tb.ppi$Synonyms.Interactor.B )
str(tb.ppi)## 'data.frame': 141640 obs. of 36 variables:
## $ X.BioGRID.Interaction.ID : int 68770 68771 68774 68775 68778 68779 68782 68783 68786 68787 ...
## $ Entrez.Gene.Interactor.A : int 851136 854020 851136 854290 851136 852582 851136 854933 851136 852607 ...
## $ Entrez.Gene.Interactor.B : int 854020 851136 854290 851136 852582 851136 854933 851136 852607 851136 ...
## $ BioGRID.ID.Interactor.A : int 31676 34272 31676 34518 31676 32973 31676 35097 31676 32996 ...
## $ BioGRID.ID.Interactor.B : int 34272 31676 34518 31676 32973 31676 35097 31676 32996 31676 ...
## $ Systematic.Name.Interactor.A: chr "YLR418C" "YOL145C" "YLR418C" "YOR123C" ...
## $ Systematic.Name.Interactor.B: chr "YOL145C" "YLR418C" "YOR123C" "YLR418C" ...
## $ Official.Symbol.Interactor.A: Factor w/ 5925 levels "1-Oct","15S_RRNA",..: 631 860 631 2072 631 2818 631 3081 631 3783 ...
## $ Official.Symbol.Interactor.B: Factor w/ 6376 levels "","1-Oct","15S_RRNA",..: 906 667 2196 667 2962 667 3236 667 3955 667 ...
## $ Synonyms.Interactor.A : Factor w/ 4432 levels "","(R","[acyl-carrier-protein] S-malonyltransferase",..: 1954 552 1954 1697 1954 1928 1954 1083 1954 700 ...
## $ Synonyms.Interactor.B : Factor w/ 4746 levels "","(R","[acyl-carrier-protein] S-malonyltransferase",..: 602 2089 1813 2089 2063 2089 1154 2089 752 2089 ...
## $ Experimental.System : Factor w/ 28 levels "","Affinity Capture-Luminescence",..: 3 3 3 3 3 3 3 3 3 3 ...
## $ Experimental.System.Type : Factor w/ 3 levels "","genetic","physical": 3 3 3 3 3 3 3 3 3 3 ...
## $ Author : Factor w/ 13744 levels "","Aalto MK (1993)",..: 6197 6197 6197 6197 6197 6197 6197 6197 6197 6197 ...
## $ Pubmed.ID : int 14759368 14759368 14759368 14759368 14759368 14759368 14759368 14759368 14759368 14759368 ...
## $ Organism.Interactor.A : int 559292 559292 559292 559292 559292 559292 559292 559292 559292 559292 ...
## $ Organism.Interactor.B : int 559292 559292 559292 559292 559292 559292 559292 559292 559292 559292 ...
## $ Throughput : Factor w/ 4 levels "","High Throughput",..: 2 2 2 2 2 2 2 2 2 2 ...
## $ Score : num NA NA NA NA NA NA NA NA NA NA ...
## $ Modification : Factor w/ 17 levels "","Acetylation",..: NA NA NA NA NA NA NA NA NA NA ...
## $ Phenotypes : Factor w/ 2172 levels "","acid pH resistance:partial rescue",..: NA NA NA NA NA NA NA NA NA NA ...
## $ Qualifications : Factor w/ 334656 levels "","(F20A","(PAB1) as a dosage suppressor of the Slg phenotype of the rpl33a G76R",..: NA NA NA NA NA NA NA NA NA NA ...
## $ Tags : logi NA NA NA NA NA NA ...
## $ Source.Database : Factor w/ 2 levels "","BIOGRID": 2 2 2 2 2 2 2 2 2 2 ...
## $ X : Factor w/ 12 levels ""," P-value = 0.0004064]|alleles: arc35-6 - act1-136 [SGA score = -0.3705",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.1 : Factor w/ 11 levels ""," P-value = 0.0001617]|alleles: pbr1-5012 - pkc1-1 [SGA score = -0.7905",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.2 : Factor w/ 10 levels ""," P-value = 0.001011]|alleles: bet4-5007 - act1-124 [SGA score = -0.2097",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.3 : Factor w/ 9 levels ""," P-value = 0.000581]|alleles: pkc1-4 - act1-136 [SGA score = -0.2153",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.4 : Factor w/ 8 levels ""," P-value = 0.001378]|alleles: arc35-6 - act1-4 [SGA score = -0.1451",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.5 : Factor w/ 8 levels ""," P-value = 0.0001648]|alleles: bet4-5007 - act1-155 [SGA score = -0.1568",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.6 : Factor w/ 6 levels ""," P-value = 0.0009274]|alleles: bet4-5007 - act1-159 [SGA score = -0.1793",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.7 : Factor w/ 5 levels ""," P-value = 0.0002055]|alleles: act1-4 - pfy1-13 [SGA score = -0.3401",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.8 : Factor w/ 4 levels ""," P-value = 0.0002784]|alleles: act1-159 - pkc1-4 [SGA score = -0.1767",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.9 : Factor w/ 3 levels ""," P-value = 0.01853]|alleles: act1-3 - pkc1-2 [SGA score = -0.2618",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.10 : Factor w/ 3 levels ""," P-value = 1.166E-9]\tNA\tBIOGRID",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.11 : Factor w/ 2 levels ""," P-value = 0.0001836]\tNA\tBIOGRID": 1 1 1 1 1 1 1 1 1 1 ...if( debug == 0) { rm(tb); }total = length(tb.ppi[,1]);
tb.ppi$ordered_pairs = NA;
for (i in 1:total ) {
if( (round(i/1000)*1000 - i)==0 ) { print(paste(i, "::", total - i) ); }
pairs = tb.ppi[i , c("Systematic.Name.Interactor.A", "Systematic.Name.Interactor.B")];
if ( is.na(pairs[1,1]) ) {
tb.ppi$ordered_pairs[i] = "NA_found";
} else {
ordered_pairs = sort(pairs)
tb.ppi$ordered_pairs[i] = paste( ordered_pairs[1,1], ordered_pairs[1,2], sep="_");
}
}## [1] "1000 :: 140640"
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## [1] "141000 :: 640"str(tb.ppi)## 'data.frame': 141640 obs. of 37 variables:
## $ X.BioGRID.Interaction.ID : int 68770 68771 68774 68775 68778 68779 68782 68783 68786 68787 ...
## $ Entrez.Gene.Interactor.A : int 851136 854020 851136 854290 851136 852582 851136 854933 851136 852607 ...
## $ Entrez.Gene.Interactor.B : int 854020 851136 854290 851136 852582 851136 854933 851136 852607 851136 ...
## $ BioGRID.ID.Interactor.A : int 31676 34272 31676 34518 31676 32973 31676 35097 31676 32996 ...
## $ BioGRID.ID.Interactor.B : int 34272 31676 34518 31676 32973 31676 35097 31676 32996 31676 ...
## $ Systematic.Name.Interactor.A: chr "YLR418C" "YOL145C" "YLR418C" "YOR123C" ...
## $ Systematic.Name.Interactor.B: chr "YOL145C" "YLR418C" "YOR123C" "YLR418C" ...
## $ Official.Symbol.Interactor.A: Factor w/ 5925 levels "1-Oct","15S_RRNA",..: 631 860 631 2072 631 2818 631 3081 631 3783 ...
## $ Official.Symbol.Interactor.B: Factor w/ 6376 levels "","1-Oct","15S_RRNA",..: 906 667 2196 667 2962 667 3236 667 3955 667 ...
## $ Synonyms.Interactor.A : Factor w/ 4432 levels "","(R","[acyl-carrier-protein] S-malonyltransferase",..: 1954 552 1954 1697 1954 1928 1954 1083 1954 700 ...
## $ Synonyms.Interactor.B : Factor w/ 4746 levels "","(R","[acyl-carrier-protein] S-malonyltransferase",..: 602 2089 1813 2089 2063 2089 1154 2089 752 2089 ...
## $ Experimental.System : Factor w/ 28 levels "","Affinity Capture-Luminescence",..: 3 3 3 3 3 3 3 3 3 3 ...
## $ Experimental.System.Type : Factor w/ 3 levels "","genetic","physical": 3 3 3 3 3 3 3 3 3 3 ...
## $ Author : Factor w/ 13744 levels "","Aalto MK (1993)",..: 6197 6197 6197 6197 6197 6197 6197 6197 6197 6197 ...
## $ Pubmed.ID : int 14759368 14759368 14759368 14759368 14759368 14759368 14759368 14759368 14759368 14759368 ...
## $ Organism.Interactor.A : int 559292 559292 559292 559292 559292 559292 559292 559292 559292 559292 ...
## $ Organism.Interactor.B : int 559292 559292 559292 559292 559292 559292 559292 559292 559292 559292 ...
## $ Throughput : Factor w/ 4 levels "","High Throughput",..: 2 2 2 2 2 2 2 2 2 2 ...
## $ Score : num NA NA NA NA NA NA NA NA NA NA ...
## $ Modification : Factor w/ 17 levels "","Acetylation",..: NA NA NA NA NA NA NA NA NA NA ...
## $ Phenotypes : Factor w/ 2172 levels "","acid pH resistance:partial rescue",..: NA NA NA NA NA NA NA NA NA NA ...
## $ Qualifications : Factor w/ 334656 levels "","(F20A","(PAB1) as a dosage suppressor of the Slg phenotype of the rpl33a G76R",..: NA NA NA NA NA NA NA NA NA NA ...
## $ Tags : logi NA NA NA NA NA NA ...
## $ Source.Database : Factor w/ 2 levels "","BIOGRID": 2 2 2 2 2 2 2 2 2 2 ...
## $ X : Factor w/ 12 levels ""," P-value = 0.0004064]|alleles: arc35-6 - act1-136 [SGA score = -0.3705",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.1 : Factor w/ 11 levels ""," P-value = 0.0001617]|alleles: pbr1-5012 - pkc1-1 [SGA score = -0.7905",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.2 : Factor w/ 10 levels ""," P-value = 0.001011]|alleles: bet4-5007 - act1-124 [SGA score = -0.2097",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.3 : Factor w/ 9 levels ""," P-value = 0.000581]|alleles: pkc1-4 - act1-136 [SGA score = -0.2153",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.4 : Factor w/ 8 levels ""," P-value = 0.001378]|alleles: arc35-6 - act1-4 [SGA score = -0.1451",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.5 : Factor w/ 8 levels ""," P-value = 0.0001648]|alleles: bet4-5007 - act1-155 [SGA score = -0.1568",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.6 : Factor w/ 6 levels ""," P-value = 0.0009274]|alleles: bet4-5007 - act1-159 [SGA score = -0.1793",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.7 : Factor w/ 5 levels ""," P-value = 0.0002055]|alleles: act1-4 - pfy1-13 [SGA score = -0.3401",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.8 : Factor w/ 4 levels ""," P-value = 0.0002784]|alleles: act1-159 - pkc1-4 [SGA score = -0.1767",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.9 : Factor w/ 3 levels ""," P-value = 0.01853]|alleles: act1-3 - pkc1-2 [SGA score = -0.2618",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.10 : Factor w/ 3 levels ""," P-value = 1.166E-9]\tNA\tBIOGRID",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ X.11 : Factor w/ 2 levels ""," P-value = 0.0001836]\tNA\tBIOGRID": 1 1 1 1 1 1 1 1 1 1 ...
## $ ordered_pairs : chr "YLR418C_YOL145C" "YLR418C_YOL145C" "YLR418C_YOR123C" "YLR418C_YOR123C" ...
How many unique biogrid PPI?
unique.ordered_pairs = unique(tb.ppi$ordered_pairs);
length( unique(tb.ppi$ordered_pairs) ) / length(tb.ppi$ordered_pairs)## [1] 0.6522522tb.ppi.unique = tb.ppi[ match(unique.ordered_pairs, tb.ppi$ordered_pairs), ];
Identify essential and nonessential genes
tb.fit = read.csv( "fitness.data/SummaryRegressionHetHom20171122.csv", colClasses=rep("character",9) );How many interactions per essential genes?
First find out interaxctions per gene, then pick the essential genes
degree = table( c( tb.ppi.unique$Systematic.Name.Interactor.A, tb.ppi.unique$Systematic.Name.Interactor.B) );
net = data.frame(degree);
names(net) = c("orf", "degree");
net$orf = as.character(net$orf);
Match essentiality to biogrid PPI
net$essentiality = tb.fit$essentiality[ match(net$orf, tb.fit$orf) ];
net.nonessential = net[net$essentiality=='nonessential', ];
net.essential = net[ net$essentiality == 'essential', ];
summary(net.nonessential)## orf degree essentiality
## Length:4910 Min. : 1.00 Length:4910
## Class :character 1st Qu.: 6.00 Class :character
## Mode :character Median : 14.00 Mode :character
## Mean : 28.27
## 3rd Qu.: 30.00
## Max. :1771.00
## NA's :838summary(net.essential);## orf degree essentiality ## Length:1894 Min. : 1.00 Length:1894 ## Class :character 1st Qu.: 17.00 Class :character ## Mode :characterMedian : 35.00Mode :character ##Mean : 52.56## 3rd Qu.: 61.00 ## Max. :2558.00 ## NA's :838
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