Mercurial > repos > jfb > kinatest_fisher_test
changeset 0:6f7fd13c1a05 draft
Uploaded
| author | jfb |
|---|---|
| date | Mon, 14 Jan 2019 11:12:59 -0500 |
| parents | |
| children | ae988a95b761 |
| files | KT-ID fisher test/7-7-fisher-galaxy_working.R KT-ID fisher test/OnlyTheRequiredSubBackFreqData.RData KT-ID fisher test/kinatestid_r_fisher.xml KT-ID fisher test/screener7-7.csv |
| diffstat | 4 files changed, 1346 insertions(+), 0 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/KT-ID fisher test/7-7-fisher-galaxy_working.R Mon Jan 14 11:12:59 2019 -0500 @@ -0,0 +1,924 @@ +oldw <- getOption("warn") +options(warn = -1) + +PositiveSubstrateList<- read.csv("substrates.csv", stringsAsFactors=FALSE) +NegativeSubstrateList<- read.csv("negatives.csv", stringsAsFactors=FALSE) +SubstrateBackgroundFrequency<- read.csv("SBF.csv", stringsAsFactors=FALSE) + +ScreenerFilename<-"screener" +screaner<-read.csv(ScreenerFilename, header = FALSE, stringsAsFactors = FALSE) + +DataFilename<-"thedata.RData" +load(DataFilename) + + +SDtableAndPercentTable<-"output1.csv" +NormalizationScore_CharacterizationTable<-"output2.csv" +SequenceScoringAndScreening<-"output3.csv" + + + + + +SiteSelectivityTable_EndogenousProbabilityMatrix_NormalizationScore_CharacterizationTable<-NormalizationScore_CharacterizationTable +FILENAME2<-NormalizationScore_CharacterizationTable +FILENAME3<-SequenceScoringAndScreening +substrates<-matrix(rep("A",times=((nrow(PositiveSubstrateList)-1)*15)),ncol = 15) + +for (i in 2:nrow(PositiveSubstrateList)) +{ + substratemotif<-PositiveSubstrateList[i,4:18] + substratemotif[8]<-"Y" + #substratemotif<-paste(substratemotif,sep = "",collapse = "") + j=i-1 + substratemotif<-unlist(substratemotif) + substrates[j,1:15]<-substratemotif +} + +substrates2<-substrates +substrates2[substrates2==""]<-"O" + +#I will make it so that all blank values in substrates get a O after I'm done with it + +# SpacesToOs<-c(""="O",) +# substrates<-SpacesToOs[substrates] + + + +#create the percent table +if (1==1){ +Column1<-substrates[,1] +Column2<-substrates[,2] +Column3<-substrates[,3] +Column4<-substrates[,4] +Column5<-substrates[,5] +Column6<-substrates[,6] +Column7<-substrates[,7] +Column8<-substrates[,8] +Column9<-substrates[,9] +Column10<-substrates[,10] +Column11<-substrates[,11] +Column12<-substrates[,12] +Column13<-substrates[,13] +Column14<-substrates[,14] +Column15<-substrates[,15] + +spaces1<-sum(Column1%in% "") +spaces2<-sum(Column2%in% "") +spaces3<-sum(Column3%in% "") +spaces4<-sum(Column4%in% "") +spaces5<-sum(Column5%in% "") +spaces6<-sum(Column6%in% "") +spaces7<-sum(Column7%in% "") +spaces8<-sum(Column8%in% "") +spaces9<-sum(Column9%in% "") +spaces10<-sum(Column10%in% "") +spaces11<-sum(Column11%in% "") +spaces12<-sum(Column12%in% "") +spaces13<-sum(Column13%in% "") +spaces14<-sum(Column14%in% "") +spaces15<-sum(Column15%in% "") +OllOs<-cbind(spaces1,spaces2,spaces3,spaces4,spaces5,spaces6,spaces7,spaces8,spaces9,spaces10,spaces11, + spaces12,spaces13,spaces14,spaces15) + +A1<-sum(Column1 %in% "A") +A2<-sum(Column2 %in% "A") +A3<-sum(Column3 %in% "A") +A4<-sum(Column4 %in% "A") +A5<-sum(Column5 %in% "A") +A6<-sum(Column6 %in% "A") +A7<-sum(Column7 %in% "A") +A8<-sum(Column8 %in% "A") +A9<-sum(Column9 %in% "A") +A10<-sum(Column10 %in% "A") +A11<-sum(Column11 %in% "A") +A12<-sum(Column12 %in% "A") +A13<-sum(Column13 %in% "A") +A14<-sum(Column14 %in% "A") +A15<-sum(Column15 %in% "A") +AllAs<-cbind(A1,A2,A3,A4,A5,A6,A7,A8,A9,A10,A11,A12,A13,A14,A15) + +C1<-sum(Column1 %in% "C") +C2<-sum(Column2 %in% "C") +C3<-sum(Column3 %in% "C") +C4<-sum(Column4 %in% "C") +C5<-sum(Column5 %in% "C") +C6<-sum(Column6 %in% "C") +C7<-sum(Column7 %in% "C") +C8<-sum(Column8 %in% "C") +C9<-sum(Column9 %in% "C") +C10<-sum(Column10 %in% "C") +C11<-sum(Column11 %in% "C") +C12<-sum(Column12 %in% "C") +C13<-sum(Column13 %in% "C") +C14<-sum(Column14 %in% "C") +C15<-sum(Column15 %in% "C") +CllCs<-cbind(C1,C2,C3,C4,C5,C6,C7,C8,C9,C10,C11,C12,C13,C14,C15) + +D1<-sum(Column1 %in% "D") +D2<-sum(Column2 %in% "D") +D3<-sum(Column3 %in% "D") +D4<-sum(Column4 %in% "D") +D5<-sum(Column5 %in% "D") +D6<-sum(Column6 %in% "D") +D7<-sum(Column7 %in% "D") +D8<-sum(Column8 %in% "D") +D9<-sum(Column9 %in% "D") +D10<-sum(Column10 %in% "D") +D11<-sum(Column11 %in% "D") +D12<-sum(Column12 %in% "D") +D13<-sum(Column13 %in% "D") +D14<-sum(Column14 %in% "D") +D15<-sum(Column15 %in% "D") +DllDs<-cbind(D1,D2,D3,D4,D5,D6,D7,D8,D9,D10,D11,D12,D13,D14,D15) + +E1<-sum(Column1 %in% "E") +E2<-sum(Column2 %in% "E") +E3<-sum(Column3 %in% "E") +E4<-sum(Column4 %in% "E") +E5<-sum(Column5 %in% "E") +E6<-sum(Column6 %in% "E") +E7<-sum(Column7 %in% "E") +E8<-sum(Column8 %in% "E") +E9<-sum(Column9 %in% "E") +E10<-sum(Column10 %in% "E") +E11<-sum(Column11 %in% "E") +E12<-sum(Column12 %in% "E") +E13<-sum(Column13 %in% "E") +E14<-sum(Column14 %in% "E") +E15<-sum(Column15 %in% "E") +EllEs<-cbind(E1,E2,E3,E4,E5,E6,E7,E8,E9,E10,E11,E12,E13,E14,E15) + +F1<-sum(Column1 %in% "F") +F2<-sum(Column2 %in% "F") +F3<-sum(Column3 %in% "F") +F4<-sum(Column4 %in% "F") +F5<-sum(Column5 %in% "F") +F6<-sum(Column6 %in% "F") +F7<-sum(Column7 %in% "F") +F8<-sum(Column8 %in% "F") +F9<-sum(Column9 %in% "F") +F10<-sum(Column10 %in% "F") +F11<-sum(Column11 %in% "F") +F12<-sum(Column12 %in% "F") +F13<-sum(Column13 %in% "F") +F14<-sum(Column14 %in% "F") +F15<-sum(Column15 %in% "F") +FllFs<-cbind(F1,F2,F3,F4,F5,F6,F7,F8,F9,F10,F11,F12,F13,F14,F15) + +G1<-sum(Column1 %in% "G") +G2<-sum(Column2 %in% "G") +G3<-sum(Column3 %in% "G") +G4<-sum(Column4 %in% "G") +G5<-sum(Column5 %in% "G") +G6<-sum(Column6 %in% "G") +G7<-sum(Column7 %in% "G") +G8<-sum(Column8 %in% "G") +G9<-sum(Column9 %in% "G") +G10<-sum(Column10 %in% "G") +G11<-sum(Column11 %in% "G") +G12<-sum(Column12 %in% "G") +G13<-sum(Column13 %in% "G") +G14<-sum(Column14 %in% "G") +G15<-sum(Column15 %in% "G") +GllGs<-cbind(G1,G2,G3,G4,G5,G6,G7,G8,G9,G10,G11,G12,G13,G14,G15) + +H1<-sum(Column1 %in% "H") +H2<-sum(Column2 %in% "H") +H3<-sum(Column3 %in% "H") +H4<-sum(Column4 %in% "H") +H5<-sum(Column5 %in% "H") +H6<-sum(Column6 %in% "H") +H7<-sum(Column7 %in% "H") +H8<-sum(Column8 %in% "H") +H9<-sum(Column9 %in% "H") +H10<-sum(Column10 %in% "H") +H11<-sum(Column11 %in% "H") +H12<-sum(Column12 %in% "H") +H13<-sum(Column13 %in% "H") +H14<-sum(Column14 %in% "H") +H15<-sum(Column15 %in% "H") +HllHs<-cbind(H1,H2,H3,H4,H5,H6,H7,H8,H9,H10,H11,H12,H13,H14,H15) + +I1<-sum(Column1 %in% "I") +I2<-sum(Column2 %in% "I") +I3<-sum(Column3 %in% "I") +I4<-sum(Column4 %in% "I") +I5<-sum(Column5 %in% "I") +I6<-sum(Column6 %in% "I") +I7<-sum(Column7 %in% "I") +I8<-sum(Column8 %in% "I") +I9<-sum(Column9 %in% "I") +I10<-sum(Column10 %in% "I") +I11<-sum(Column11 %in% "I") +I12<-sum(Column12 %in% "I") +I13<-sum(Column13 %in% "I") +I14<-sum(Column14 %in% "I") +I15<-sum(Column15 %in% "I") +IllIs<-cbind(I1,I2,I3,I4,I5,I6,I7,I8,I9,I10,I11,I12,I13,I14,I15) + +K1<-sum(Column1 %in% "K") +K2<-sum(Column2 %in% "K") +K3<-sum(Column3 %in% "K") +K4<-sum(Column4 %in% "K") +K5<-sum(Column5 %in% "K") +K6<-sum(Column6 %in% "K") +K7<-sum(Column7 %in% "K") +K8<-sum(Column8 %in% "K") +K9<-sum(Column9 %in% "K") +K10<-sum(Column10 %in% "K") +K11<-sum(Column11 %in% "K") +K12<-sum(Column12 %in% "K") +K13<-sum(Column13 %in% "K") +K14<-sum(Column14 %in% "K") +K15<-sum(Column15 %in% "K") +KllKs<-cbind(K1,K2,K3,K4,K5,K6,K7,K8,K9,K10,K11,K12,K13,K14,K15) + +L1<-sum(Column1 %in% "L") +L2<-sum(Column2 %in% "L") +L3<-sum(Column3 %in% "L") +L4<-sum(Column4 %in% "L") +L5<-sum(Column5 %in% "L") +L6<-sum(Column6 %in% "L") +L7<-sum(Column7 %in% "L") +L8<-sum(Column8 %in% "L") +L9<-sum(Column9 %in% "L") +L10<-sum(Column10 %in% "L") +L11<-sum(Column11 %in% "L") +L12<-sum(Column12 %in% "L") +L13<-sum(Column13 %in% "L") +L14<-sum(Column14 %in% "L") +L15<-sum(Column15 %in% "L") +LllLs<-cbind(L1,L2,L3,L4,L5,L6,L7,L8,L9,L10,L11,L12,L13,L14,L15) + +M1<-sum(Column1 %in% "M") +M2<-sum(Column2 %in% "M") +M3<-sum(Column3 %in% "M") +M4<-sum(Column4 %in% "M") +M5<-sum(Column5 %in% "M") +M6<-sum(Column6 %in% "M") +M7<-sum(Column7 %in% "M") +M8<-sum(Column8 %in% "M") +M9<-sum(Column9 %in% "M") +M10<-sum(Column10 %in% "M") +M11<-sum(Column11 %in% "M") +M12<-sum(Column12 %in% "M") +M13<-sum(Column13 %in% "M") +M14<-sum(Column14 %in% "M") +M15<-sum(Column15 %in% "M") +MllMs<-cbind(M1,M2,M3,M4,M5,M6,M7,M8,M9,M10,M11,M12,M13,M14,M15) + +N1<-sum(Column1 %in% "N") +N2<-sum(Column2 %in% "N") +N3<-sum(Column3 %in% "N") +N4<-sum(Column4 %in% "N") +N5<-sum(Column5 %in% "N") +N6<-sum(Column6 %in% "N") +N7<-sum(Column7 %in% "N") +N8<-sum(Column8 %in% "N") +N9<-sum(Column9 %in% "N") +N10<-sum(Column10 %in% "N") +N11<-sum(Column11 %in% "N") +N12<-sum(Column12 %in% "N") +N13<-sum(Column13 %in% "N") +N14<-sum(Column14 %in% "N") +N15<-sum(Column15 %in% "N") +NllNs<-cbind(N1,N2,N3,N4,N5,N6,N7,N8,N9,N10,N11,N12,N13,N14,N15) + +P1<-sum(Column1 %in% "P") +P2<-sum(Column2 %in% "P") +P3<-sum(Column3 %in% "P") +P4<-sum(Column4 %in% "P") +P5<-sum(Column5 %in% "P") +P6<-sum(Column6 %in% "P") +P7<-sum(Column7 %in% "P") +P8<-sum(Column8 %in% "P") +P9<-sum(Column9 %in% "P") +P10<-sum(Column10 %in% "P") +P11<-sum(Column11 %in% "P") +P12<-sum(Column12 %in% "P") +P13<-sum(Column13 %in% "P") +P14<-sum(Column14 %in% "P") +P15<-sum(Column15 %in% "P") +PllPs<-cbind(P1,P2,P3,P4,P5,P6,P7,P8,P9,P10,P11,P12,P13,P14,P15) + +Q1<-sum(Column1 %in% "Q") +Q2<-sum(Column2 %in% "Q") +Q3<-sum(Column3 %in% "Q") +Q4<-sum(Column4 %in% "Q") +Q5<-sum(Column5 %in% "Q") +Q6<-sum(Column6 %in% "Q") +Q7<-sum(Column7 %in% "Q") +Q8<-sum(Column8 %in% "Q") +Q9<-sum(Column9 %in% "Q") +Q10<-sum(Column10 %in% "Q") +Q11<-sum(Column11 %in% "Q") +Q12<-sum(Column12 %in% "Q") +Q13<-sum(Column13 %in% "Q") +Q14<-sum(Column14 %in% "Q") +Q15<-sum(Column15 %in% "Q") +QllQs<-cbind(Q1,Q2,Q3,Q4,Q5,Q6,Q7,Q8,Q9,Q10,Q11,Q12,Q13,Q14,Q15) + +R1<-sum(Column1 %in% "R") +R2<-sum(Column2 %in% "R") +R3<-sum(Column3 %in% "R") +R4<-sum(Column4 %in% "R") +R5<-sum(Column5 %in% "R") +R6<-sum(Column6 %in% "R") +R7<-sum(Column7 %in% "R") +R8<-sum(Column8 %in% "R") +R9<-sum(Column9 %in% "R") +R10<-sum(Column10 %in% "R") +R11<-sum(Column11 %in% "R") +R12<-sum(Column12 %in% "R") +R13<-sum(Column13 %in% "R") +R14<-sum(Column14 %in% "R") +R15<-sum(Column15 %in% "R") +RllRs<-cbind(R1,R2,R3,R4,R5,R6,R7,R8,R9,R10,R11,R12,R13,R14,R15) + +S1<-sum(Column1 %in% "S") +S2<-sum(Column2 %in% "S") +S3<-sum(Column3 %in% "S") +S4<-sum(Column4 %in% "S") +S5<-sum(Column5 %in% "S") +S6<-sum(Column6 %in% "S") +S7<-sum(Column7 %in% "S") +S8<-sum(Column8 %in% "S") +S9<-sum(Column9 %in% "S") +S10<-sum(Column10 %in% "S") +S11<-sum(Column11 %in% "S") +S12<-sum(Column12 %in% "S") +S13<-sum(Column13 %in% "S") +S14<-sum(Column14 %in% "S") +S15<-sum(Column15 %in% "S") +SllSs<-cbind(S1,S2,S3,S4,S5,S6,S7,S8,S9,S10,S11,S12,S13,S14,S15) + +T1<-sum(Column1 %in% "T") +T2<-sum(Column2 %in% "T") +T3<-sum(Column3 %in% "T") +T4<-sum(Column4 %in% "T") +T5<-sum(Column5 %in% "T") +T6<-sum(Column6 %in% "T") +T7<-sum(Column7 %in% "T") +T8<-sum(Column8 %in% "T") +T9<-sum(Column9 %in% "T") +T10<-sum(Column10 %in% "T") +T11<-sum(Column11 %in% "T") +T12<-sum(Column12 %in% "T") +T13<-sum(Column13 %in% "T") +T14<-sum(Column14 %in% "T") +T15<-sum(Column15 %in% "T") +TllTs<-cbind(T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15) + +V1<-sum(Column1 %in% "V") +V2<-sum(Column2 %in% "V") +V3<-sum(Column3 %in% "V") +V4<-sum(Column4 %in% "V") +V5<-sum(Column5 %in% "V") +V6<-sum(Column6 %in% "V") +V7<-sum(Column7 %in% "V") +V8<-sum(Column8 %in% "V") +V9<-sum(Column9 %in% "V") +V10<-sum(Column10 %in% "V") +V11<-sum(Column11 %in% "V") +V12<-sum(Column12 %in% "V") +V13<-sum(Column13 %in% "V") +V14<-sum(Column14 %in% "V") +V15<-sum(Column15 %in% "V") +VllVs<-cbind(V1,V2,V3,V4,V5,V6,V7,V8,V9,V10,V11,V12,V13,V14,V15) + +W1<-sum(Column1 %in% "W") +W2<-sum(Column2 %in% "W") +W3<-sum(Column3 %in% "W") +W4<-sum(Column4 %in% "W") +W5<-sum(Column5 %in% "W") +W6<-sum(Column6 %in% "W") +W7<-sum(Column7 %in% "W") +W8<-sum(Column8 %in% "W") +W9<-sum(Column9 %in% "W") +W10<-sum(Column10 %in% "W") +W11<-sum(Column11 %in% "W") +W12<-sum(Column12 %in% "W") +W13<-sum(Column13 %in% "W") +W14<-sum(Column14 %in% "W") +W15<-sum(Column15 %in% "W") +WllWs<-cbind(W1,W2,W3,W4,W5,W6,W7,W8,W9,W10,W11,W12,W13,W14,W15) + +Y1<-sum(Column1 %in% "Y") +Y2<-sum(Column2 %in% "Y") +Y3<-sum(Column3 %in% "Y") +Y4<-sum(Column4 %in% "Y") +Y5<-sum(Column5 %in% "Y") +Y6<-sum(Column6 %in% "Y") +Y7<-sum(Column7 %in% "Y") +Y8<-sum(Column8 %in% "Y") +Y9<-sum(Column9 %in% "Y") +Y10<-sum(Column10 %in% "Y") +Y11<-sum(Column11 %in% "Y") +Y12<-sum(Column12 %in% "Y") +Y13<-sum(Column13 %in% "Y") +Y14<-sum(Column14 %in% "Y") +Y15<-sum(Column15 %in% "Y") +YllYs<-cbind(Y1,Y2,Y3,Y4,Y5,Y6,Y7,Y8,Y9,Y10,Y11,Y12,Y13,Y14,Y15) +} +#this is substrate percents + +#A C D E F G H I K L N P Q R S T V W Y O + +AllSubBackFreq<-array(data = NA,dim = c(21,15,nrow(SubstrateBackgroundFrequency))) +# vectorvictor<-rep(1,times=nrow(SubstrateBackgroundFrequency)) +# AllSubBackFreq[20,5,]<-vectorvictor +#this is where I'm creating the new SubBackFreq table, I have a list with all possible SBF matrices, +#I perform a for function to find all the matrices that are in Substrate Background Frequency +#and place them all in this array, then I will do mean and SD +AAccessionNumbers<-SubstrateBackgroundFrequency[,1] +AllGeneNames<-names(Genelist) + +number_replaced<-0 +totalmotifs<-0 +for (z in 1:length(AAccessionNumbers)) { + pattern<-AAccessionNumbers[z] + referencepoint<-grepl(pattern = pattern, x=AllGeneNames,fixed = TRUE) + #so take the accession number and find which matrix corresponds to that accession number + referencenumber<-which(referencepoint==TRUE) + if (length(referencenumber)<1){referencenumber<-FALSE} + # if (referencenumber==FALSE) + # ThisMatix<-array(data=NA, dim = c(21,9)) + if (referencenumber!=FALSE){ + print(referencenumber) + motifs<-unlist(Genelist[[referencenumber]]) + therow<-c(1:15) + for (a in 1:length(motifs)) { + thecut<-unlist(strsplit(motifs[a], split="")) + edges<-c("O","O","O","O","O","O","O") + thecut<-c(edges,thecut,edges) + theYs<-which(thecut=="Y") + for (q in 1:length(theYs)) { + thiscut<-thecut[(theYs[q]-7):(theYs[q]+7)] + therow<-rbind(therow,thiscut) + totalmotifs<-totalmotifs+1 + } + } + + #I hate for loops but I'm doing them anyway + + cutreplacement<-c("X","X","X","X","X","X","X","X","X","X","X","X","X","X","X") + for (t in 1:nrow(therow)) { + compare1<-therow[t,1:15] + compare1<-paste(compare1,sep = "",collapse = "") + + for (v in 1:nrow(substrates2)) { + positivesubstrate<-substrates2[v,1:15] + positivesubstrate<-paste(positivesubstrate,sep = "",collapse = "") + + if (compare1==positivesubstrate){ + therow[t,1:15]<-cutreplacement + number_replaced<-number_replaced+1 + } + } + + } + + #remember here + #here's what I want to do: every motif gets archived individually as how many AAs are left and right + #of the Y, THEN I take SD and Mean of that?!?!?! + #... no. I'M GOING TO SUM UP ALL THE INDIVIDUAL AAs AT EACH POSITION + #then divide them by total number of motifs + #then just divide percent table by that + #then find out if it's significant with a test + Column1<-therow[,1] + Column2<-therow[,2] + Column3<-therow[,3] + Column4<-therow[,4] + Column5<-therow[,5] + Column6<-therow[,6] + Column7<-therow[,7] + Column8<-therow[,8] + Column9<-therow[,9] + Column10<-therow[,10] + Column11<-therow[,11] + Column12<-therow[,12] + Column13<-therow[,13] + Column14<-therow[,14] + Column15<-therow[,15] + slice1<-c(sum(Column1=="A"),sum(Column1=="C"),sum(Column1=="D"),sum(Column1=="E"),sum(Column1=="F"), + sum(Column1=="G"),sum(Column1=="H"),sum(Column1=="I"),sum(Column1=="K"),sum(Column1=="L"), + sum(Column1=="M"),sum(Column1=="N"),sum(Column1=="P"),sum(Column1=="Q"),sum(Column1=="R"), + sum(Column1=="S"),sum(Column1=="T"),sum(Column1=="V"),sum(Column1=="W"),sum(Column1=="Y"), + sum(Column1=="O")) + slice2<-c(sum(Column2=="A"),sum(Column2=="C"),sum(Column2=="D"),sum(Column2=="E"),sum(Column2=="F"), + sum(Column2=="G"),sum(Column2=="H"),sum(Column2=="I"),sum(Column2=="K"),sum(Column2=="L"), + sum(Column2=="M"),sum(Column2=="N"),sum(Column2=="P"),sum(Column2=="Q"),sum(Column2=="R"), + sum(Column2=="S"),sum(Column2=="T"),sum(Column2=="V"),sum(Column2=="W"),sum(Column2=="Y"), + sum(Column2=="O")) + slice3<-c(sum(Column3=="A"),sum(Column3=="C"),sum(Column3=="D"),sum(Column3=="E"),sum(Column3=="F"), + sum(Column3=="G"),sum(Column3=="H"),sum(Column3=="I"),sum(Column3=="K"),sum(Column3=="L"), + sum(Column3=="M"),sum(Column3=="N"),sum(Column3=="P"),sum(Column3=="Q"),sum(Column3=="R"), + sum(Column3=="S"),sum(Column3=="T"),sum(Column3=="V"),sum(Column3=="W"),sum(Column3=="Y"), + sum(Column3=="O")) + slice4<-c(sum(Column4=="A"),sum(Column4=="C"),sum(Column4=="D"),sum(Column4=="E"),sum(Column4=="F"), + sum(Column4=="G"),sum(Column4=="H"),sum(Column4=="I"),sum(Column4=="K"),sum(Column4=="L"), + sum(Column4=="M"),sum(Column4=="N"),sum(Column4=="P"),sum(Column4=="Q"),sum(Column4=="R"), + sum(Column4=="S"),sum(Column4=="T"),sum(Column4=="V"),sum(Column4=="W"),sum(Column4=="Y"), + sum(Column4=="O")) + slice5<-c(sum(Column5=="A"),sum(Column5=="C"),sum(Column5=="D"),sum(Column5=="E"),sum(Column5=="F"), + sum(Column5=="G"),sum(Column5=="H"),sum(Column5=="I"),sum(Column5=="K"),sum(Column5=="L"), + sum(Column5=="M"),sum(Column5=="N"),sum(Column5=="P"),sum(Column5=="Q"),sum(Column5=="R"), + sum(Column5=="S"),sum(Column5=="T"),sum(Column5=="V"),sum(Column5=="W"),sum(Column5=="Y"), + sum(Column5=="O")) + slice6<-c(sum(Column6=="A"),sum(Column6=="C"),sum(Column6=="D"),sum(Column6=="E"),sum(Column6=="F"), + sum(Column6=="G"),sum(Column6=="H"),sum(Column6=="I"),sum(Column6=="K"),sum(Column6=="L"), + sum(Column6=="M"),sum(Column6=="N"),sum(Column6=="P"),sum(Column6=="Q"),sum(Column6=="R"), + sum(Column6=="S"),sum(Column6=="T"),sum(Column6=="V"),sum(Column6=="W"),sum(Column6=="Y"), + sum(Column6=="O")) + slice7<-c(sum(Column7=="A"),sum(Column7=="C"),sum(Column7=="D"),sum(Column7=="E"),sum(Column7=="F"), + sum(Column7=="G"),sum(Column7=="H"),sum(Column7=="I"),sum(Column7=="K"),sum(Column7=="L"), + sum(Column7=="M"),sum(Column7=="N"),sum(Column7=="P"),sum(Column7=="Q"),sum(Column7=="R"), + sum(Column7=="S"),sum(Column7=="T"),sum(Column7=="V"),sum(Column7=="W"),sum(Column7=="Y"), + sum(Column7=="O")) + slice8<-c(sum(Column8=="A"),sum(Column8=="C"),sum(Column8=="D"),sum(Column8=="E"),sum(Column8=="F"), + sum(Column8=="G"),sum(Column8=="H"),sum(Column8=="I"),sum(Column8=="K"),sum(Column8=="L"), + sum(Column8=="M"),sum(Column8=="N"),sum(Column8=="P"),sum(Column8=="Q"),sum(Column8=="R"), + sum(Column8=="S"),sum(Column8=="T"),sum(Column8=="V"),sum(Column8=="W"),sum(Column8=="Y"), + sum(Column8=="O")) + slice9<-c(sum(Column9=="A"),sum(Column9=="C"),sum(Column9=="D"),sum(Column9=="E"),sum(Column9=="F"), + sum(Column9=="G"),sum(Column9=="H"),sum(Column9=="I"),sum(Column9=="K"),sum(Column9=="L"), + sum(Column9=="M"),sum(Column9=="N"),sum(Column9=="P"),sum(Column9=="Q"),sum(Column9=="R"), + sum(Column9=="S"),sum(Column9=="T"),sum(Column9=="V"),sum(Column9=="W"),sum(Column9=="Y"), + sum(Column9=="O")) + slice10<-c(sum(Column10=="A"),sum(Column10=="C"),sum(Column10=="D"),sum(Column10=="E"),sum(Column10=="F"), + sum(Column10=="G"),sum(Column10=="H"),sum(Column10=="I"),sum(Column10=="K"),sum(Column10=="L"), + sum(Column10=="M"),sum(Column10=="N"),sum(Column10=="P"),sum(Column10=="Q"),sum(Column10=="R"), + sum(Column10=="S"),sum(Column10=="T"),sum(Column10=="V"),sum(Column10=="W"),sum(Column10=="Y"), + sum(Column10=="O")) + slice11<-c(sum(Column11=="A"),sum(Column11=="C"),sum(Column11=="D"),sum(Column11=="E"),sum(Column11=="F"), + sum(Column11=="G"),sum(Column11=="H"),sum(Column11=="I"),sum(Column11=="K"),sum(Column11=="L"), + sum(Column11=="M"),sum(Column11=="N"),sum(Column11=="P"),sum(Column11=="Q"),sum(Column11=="R"), + sum(Column11=="S"),sum(Column11=="T"),sum(Column11=="V"),sum(Column11=="W"),sum(Column11=="Y"), + sum(Column11=="O")) + slice12<-c(sum(Column12=="A"),sum(Column12=="C"),sum(Column12=="D"),sum(Column12=="E"),sum(Column12=="F"), + sum(Column12=="G"),sum(Column12=="H"),sum(Column12=="I"),sum(Column12=="K"),sum(Column12=="L"), + sum(Column12=="M"),sum(Column12=="N"),sum(Column12=="P"),sum(Column12=="Q"),sum(Column12=="R"), + sum(Column12=="S"),sum(Column12=="T"),sum(Column12=="V"),sum(Column12=="W"),sum(Column12=="Y"), + sum(Column12=="O")) + slice13<-c(sum(Column13=="A"),sum(Column13=="C"),sum(Column13=="D"),sum(Column13=="E"),sum(Column13=="F"), + sum(Column13=="G"),sum(Column13=="H"),sum(Column13=="I"),sum(Column13=="K"),sum(Column13=="L"), + sum(Column13=="M"),sum(Column13=="N"),sum(Column13=="P"),sum(Column13=="Q"),sum(Column13=="R"), + sum(Column13=="S"),sum(Column13=="T"),sum(Column13=="V"),sum(Column13=="W"),sum(Column13=="Y"), + sum(Column13=="O")) + slice14<-c(sum(Column14=="A"),sum(Column14=="C"),sum(Column14=="D"),sum(Column14=="E"),sum(Column14=="F"), + sum(Column14=="G"),sum(Column14=="H"),sum(Column14=="I"),sum(Column14=="K"),sum(Column14=="L"), + sum(Column14=="M"),sum(Column14=="N"),sum(Column14=="P"),sum(Column14=="Q"),sum(Column14=="R"), + sum(Column14=="S"),sum(Column14=="T"),sum(Column14=="V"),sum(Column14=="W"),sum(Column14=="Y"), + sum(Column14=="O")) + slice15<-c(sum(Column15=="A"),sum(Column15=="C"),sum(Column15=="D"),sum(Column15=="E"),sum(Column15=="F"), + sum(Column15=="G"),sum(Column15=="H"),sum(Column15=="I"),sum(Column15=="K"),sum(Column15=="L"), + sum(Column15=="M"),sum(Column15=="N"),sum(Column15=="P"),sum(Column15=="Q"),sum(Column15=="R"), + sum(Column15=="S"),sum(Column15=="T"),sum(Column15=="V"),sum(Column15=="W"),sum(Column15=="Y"), + sum(Column15=="O")) + ThisMatix<-cbind(slice1,slice2,slice3,slice4,slice5,slice6,slice7,slice8,slice9, + slice10,slice11,slice12,slice13,slice14,slice15) + ThisMatix<-ThisMatix + AllSubBackFreq[1:21,1:15,z]<-ThisMatix + } +} + +theletters<-c("A","C","D","E","F","G","H","I","K","L","M","N","P","Q","R","S","T","V","W","Y","O") +# +# AllSds<-apply(AllSubBackFreq, c(1,2), sd, na.rm = TRUE) +# AllMeans<-apply(AllSubBackFreq, c(1,2), mean, na.rm = TRUE) +#totalmotifs +SumSBF<-apply(AllSubBackFreq, c(1,2), sum, na.rm=TRUE) +# SumSBF<-SumSBF/totalmotifs + +########## +#NumeratedPeptides<-sapply(LetteredPeptides, function(y) gsub("A",A,y,perl = TRUE)) +#ReferencePoints<-sapply(ReferencePoints,grepl, pattern = AAccessionNumbers, AllGeneNames,fixed = TRUE) +######### +#nrow(substrates) +PercentTable<-rbind(AllAs,CllCs,DllDs,EllEs,FllFs,GllGs,HllHs,IllIs,KllKs,LllLs,MllMs,NllNs,PllPs,QllQs,RllRs,SllSs,TllTs,VllVs,WllWs,YllYs,OllOs) +#PercentTable<-PercentTable*100 + +fisheroddstable<-matrix(data = 1,nrow = 21,ncol = 15) +fisherpvalstable<-matrix(data = 1,nrow = 21,ncol = 15) +fisherpvalstableadjusted<-matrix(data = 1,nrow = 21,ncol = 15) +for (rowas in 1:21) { + for (colams in 1:15) { + fishermatrix<-matrix(data=c(PercentTable[rowas,colams],nrow(substrates),SumSBF[rowas,colams],(totalmotifs-number_replaced)),nrow = 2) + thetest<-fisher.test(x=fishermatrix) + fisheroddstable[rowas,colams]<-thetest$estimate + fisherpvalstable[rowas,colams]<-thetest$p.value + fisherpvalstableadjusted[rowas,colams]<-p.adjust(p=thetest$p.value,method = "fdr",n=21*15) + } +} + +# FisherPowerTable<-matrix(data = 1,nrow = 21,ncol = 9) +# for (rowas in 1:21) { +# for (colams in 1:9) { +# pro1<-PercentTable[rowas,colams]/nrow(substrates) +# pro2<-SumSBF[rowas,colams]/totalmotifs +# PowerFisherTest<-power.fisher.test(pro1,pro2,nrow(substrates),totalmotifs) +# FisherPowerTable[rowas,colams]<-PowerFisherTest +# } +# } + +fisheroddstable<-cbind.data.frame(theletters,fisheroddstable) +fisherpvalstable<-cbind.data.frame(theletters,fisherpvalstable) +fisherpvalstableadjusted<-cbind.data.frame(theletters,fisherpvalstableadjusted) + +fisherupdown<-fisheroddstable + +for (x in 1:21) { + for (y in 2:16) { + theval<-1 + testval<-fisheroddstable[x,y] + testp<-fisherpvalstable[x,y] + if (testp<.05){ + theval<-testval + } + fisherupdown[x,y]<-theval + } +} + +write.table(x="Fisher Odds, only significant ones",file = SDtableAndPercentTable, append = TRUE,sep = ",",col.names = FALSE,row.names = FALSE) +write.table(x=fisherupdown,file = SDtableAndPercentTable, append = TRUE,sep = ",",col.names = FALSE,row.names = FALSE) +write.table(x="Fisher Odds",file = SDtableAndPercentTable, append = TRUE,sep = ",",col.names = FALSE,row.names = FALSE) +write.table(x=fisheroddstable,file = SDtableAndPercentTable, append = TRUE,sep = ",",col.names = FALSE,row.names = FALSE) +write.table(x="Fisher p.values",file = SDtableAndPercentTable, append = TRUE,sep = ",",col.names = FALSE,row.names = FALSE) +write.table(x=fisherpvalstable,file = SDtableAndPercentTable, append = TRUE,sep = ",",col.names = FALSE,row.names = FALSE) +write.table(x="Fisher p.values adjusted",file = SDtableAndPercentTable, append = TRUE,sep = ",",col.names = FALSE,row.names = FALSE) +write.table(x=fisherpvalstableadjusted,file = SDtableAndPercentTable, append = TRUE,sep = ",",col.names = FALSE,row.names = FALSE) +# write.table(x="Fisher Power",file = SDtableAndPercentTable, append = TRUE,sep = ",") +# write.table(x=FisherPowerTable,file = SDtableAndPercentTable, append = TRUE,sep = ",") + +SetOfAAs<-c("Letter","A","C","D","E","F","G","H","I","K","L","M","N","P","Q","R","S","T","V","W","Y") + + +SetOfAAs<-matrix(data = SetOfAAs,ncol = 1) + +numberofY<-as.numeric(SubstrateBackgroundFrequency$Number.of.Y) +numberofY<-numberofY[!is.na(numberofY)] + +numberofPY<-as.numeric(SubstrateBackgroundFrequency$Number.of.pY) +numberofPY<-numberofPY[!is.na(numberofPY)] + +NormalizationScore<-sum(numberofPY)/sum(numberofY) + +#positions<-matrix(data = NA, nrow=20,ncol = 9) + +# write.xlsx(SDtable,file=SDtableAndPercentTable, sheetName = "Standard Deviation Table",col.names = FALSE,row.names = FALSE,append = TRUE) +# write.xlsx(PercentTable,file = SDtableAndPercentTable,sheetName = "Percent Table",col.names = FALSE,row.names = FALSE,append = TRUE) +# write.xlsx(SelectivitySheet,file = SDtableAndPercentTable,sheetName = "Site Selectivity",col.names = FALSE,row.names = FALSE,append = TRUE) +# write.xlsx(EPMtable,file=SDtableAndPercentTable,sheetName = "Endogenous Probability Matrix",col.names = FALSE,row.names = FALSE,append = TRUE) +# write.xlsx(NormalizationScore,file = SDtableAndPercentTable,sheetName = "Normalization Score",col.names = FALSE,row.names = FALSE,append = TRUE) + +NormalizationScore<-c("Normalization Score",NormalizationScore) + +# write.table(x=c("SD Table"),file=SDtableAndPercentTable,append = TRUE,sep=",", row.names = FALSE, col.names = FALSE) +# write.table(SDtable,file=SDtableAndPercentTable,append = TRUE,sep=",", row.names = FALSE, col.names = FALSE) +# write.table(x=c("Percent Table"),file=SDtableAndPercentTable,append = TRUE,sep=",", row.names = FALSE, col.names = FALSE) +# write.table(PercentTable,file=SDtableAndPercentTable, append = TRUE,sep=",",row.names = FALSE, col.names = FALSE) + +# write.table(SelectivitySheet,file = SiteSelectivityTable_EndogenousProbabilityMatrix_NormalizationScore_CharacterizationTable, append = TRUE,sep = ",",row.names = FALSE, col.names = FALSE) +# write.table(x=c("Endogenous Probability Matrix"),file=SiteSelectivityTable_EndogenousProbabilityMatrix_NormalizationScore_CharacterizationTable,append = TRUE,sep=",", row.names = FALSE, col.names = FALSE) +# write.table(EPMtable,file = SiteSelectivityTable_EndogenousProbabilityMatrix_NormalizationScore_CharacterizationTable, append = TRUE,sep = ",",row.names = FALSE, col.names = FALSE) +write.table(NormalizationScore, file = SiteSelectivityTable_EndogenousProbabilityMatrix_NormalizationScore_CharacterizationTable, append = TRUE,sep = ",",row.names = FALSE, col.names = FALSE) + +###################################### + +#change this +WhichKinase<-"Btk" + +#change this +#Positionm6<-c("E") -6 -4 1 5 6 score from -7-7 and -4-4 and the little MCC table things + +bareSDs<-fisherupdown[1:20,2:16] +bareSDs[20,8]<-3 +bareSDs[3:4,2]<-1 +bareSDs[3:4,4]<-1 +bareSDs[3:4,9]<-1 +bareSDs[3:4,13:14]<-1 + +goodones<-bareSDs>1 +bareSDs[20,8]<-1 + +allSDs<-fisheroddstable[1:20,2:16] +allSDs[3:4,2]<-1 +allSDs[3:4,4]<-1 +allSDs[3:4,9]<-1 +allSDs[3:4,13:14]<-1 + +#I'm trying to make it so it only goes 6 to 6 instead of 7 to 7, do this for speed reasons + +#what the above and below code does is this: fisherupdown is the "SD" table because it shows which positions and which amino acids the kinase likes and dislikes +#so then I use the if and which statements below to automatically pick out WHICH amino acids the kinase likes at each position, if there are less than 2 there +#I make sure there are at least 2. And I make sure that D and E are always represented as possibilities for the purposes of the terbium binding test + + +A=1 +C=2 +D=3 +E=4 +F=5 +G=6 +H=7 +I=8 +K=9 +L=10 +M=11 +N=12 +P=13 +Q=14 +R=15 +S=16 +T=17 +V=18 +W=19 +Y=20 + +aa_props <- c("A"=A, "C"=C, "D"=D, "E"=E, "F"=F,"G"=G,"H"=H,"I"=I,"K"=K,"L"=L,"M"=M,"N"=N,"P"=P,"Q"=Q,"R"=R, + "S"=S,"T"=T,"V"=V,"W"=W,"Y"=Y,"xY"=Y,"O"=21) + +ThisKinTable<-fisheroddstable + +NegativeScores<-rep(NA,times=nrow(NegativeSubstrateList)) +NegativeWeirdScores<-rep(NA,times=nrow(NegativeSubstrateList)) +for (v in 1:nrow(NegativeSubstrateList)) { + motif<-NegativeSubstrateList[v,2] + motif<-unlist(strsplit(motif,"")) + #if (length(motif)<9){print(v)}} + # motif[1] <- sapply(motif[1], function (x) aa_props[x]) + # motif[2] <- sapply(motif[2], function (x) aa_props[x]) + # motif[3] <- sapply(motif[3], function (x) aa_props[x]) + # motif[4] <- sapply(motif[4], function (x) aa_props[x]) + # motif[5] <- sapply(motif[5], function (x) aa_props[x]) + # motif[6] <- sapply(motif[6], function (x) aa_props[x]) + # motif[7] <- sapply(motif[7], function (x) aa_props[x]) + # motif[8] <- sapply(motif[8], function (x) aa_props[x]) + # motif[9] <- sapply(motif[9], function (x) aa_props[x]) + motif<- gsub(" ","O",motif) + motif <- sapply(motif, function (x) aa_props[x]) + Scoringpeptide<-motif + Scoringpeptide<-Scoringpeptide + ThisKinTableScore<-as.numeric(ThisKinTable[Scoringpeptide[1],2])*ThisKinTable[as.numeric(Scoringpeptide[2]),3]*ThisKinTable[as.numeric(Scoringpeptide[3]),4]* + ThisKinTable[as.numeric(Scoringpeptide[4]),5]*ThisKinTable[as.numeric(Scoringpeptide[5]),6]*ThisKinTable[as.numeric(Scoringpeptide[6]),7]* + ThisKinTable[as.numeric(Scoringpeptide[7]),8]* + #ThisKinTable[as.numeric(Scoringpeptide[8]),10]* + ThisKinTable[as.numeric(Scoringpeptide[9]),10]*ThisKinTable[as.numeric(Scoringpeptide[10]),11]*ThisKinTable[as.numeric(Scoringpeptide[11]),12]* + ThisKinTable[as.numeric(Scoringpeptide[12]),13]*ThisKinTable[as.numeric(Scoringpeptide[13]),14]*ThisKinTable[as.numeric(Scoringpeptide[14]),15]* + ThisKinTable[as.numeric(Scoringpeptide[15]),16] + NegativeScores[v]<-ThisKinTableScore + ThisKinTableScore<-(ThisKinTableScore/(ThisKinTableScore+1/as.numeric(NormalizationScore[2]))) + NegativeWeirdScores[v]<-ThisKinTableScore*100 +} + +negativesubstrates<-NegativeSubstrateList[,2] +NegativeWithScores<-cbind(negativesubstrates,as.character(NegativeScores),as.character(NegativeWeirdScores)) + + +#NEED TO HAVE THE NEGATIVE SUBSTRATES BE OUTPUTTED + +PositiveScores<-rep(NA,times=nrow(PositiveSubstrateList)) +PositiveWeirdScores<-rep(NA,times=nrow(PositiveSubstrateList)) + +for (v in 1:nrow(PositiveSubstrateList)) { + motif<-PositiveSubstrateList[v,4:18] + motif<-unlist(motif) + motif<- gsub("^$","O",motif) + motif <- sapply(motif, function (x) aa_props[x]) + Scoringpeptide<-motif + Scoringpeptide<-Scoringpeptide + ThisKinTableScore<-as.numeric(ThisKinTable[Scoringpeptide[1],2])*ThisKinTable[as.numeric(Scoringpeptide[2]),3]*ThisKinTable[as.numeric(Scoringpeptide[3]),4]* + ThisKinTable[as.numeric(Scoringpeptide[4]),5]*ThisKinTable[as.numeric(Scoringpeptide[5]),6]*ThisKinTable[as.numeric(Scoringpeptide[6]),7]* + ThisKinTable[as.numeric(Scoringpeptide[7]),8]* + #ThisKinTable[as.numeric(Scoringpeptide[8]),10]* + ThisKinTable[as.numeric(Scoringpeptide[9]),10]*ThisKinTable[as.numeric(Scoringpeptide[10]),11]*ThisKinTable[as.numeric(Scoringpeptide[11]),12]* + ThisKinTable[as.numeric(Scoringpeptide[12]),13]*ThisKinTable[as.numeric(Scoringpeptide[13]),14]*ThisKinTable[as.numeric(Scoringpeptide[14]),15]* + ThisKinTable[as.numeric(Scoringpeptide[15]),16] + + PositiveScores[v]<-ThisKinTableScore + ThisKinTableScore<-(ThisKinTableScore/(ThisKinTableScore+1/as.numeric(NormalizationScore[2]))) + PositiveWeirdScores[v]<-ThisKinTableScore*100 +} + +positivesubstrates<-PositiveSubstrateList[,4:18] +positivewithscores<-cbind.data.frame(positivesubstrates,PositiveScores,PositiveWeirdScores) + + + +SetOfAAs<-c("Letter","A","C","D","E","F","G","H","I","K","L","M","N","P","Q","R","S","T","V","W","Y") +SumOfSigmaAAs<-c(1:15) + +for (i in 1:15){ + SumOfSigmasValue<-0 + for (j in 1:20){ + value<-0 + if (bareSDs[j,i]>1){ + k<-j+1 + value<-sum(substrates[,i]==SetOfAAs[k]) + } + SumOfSigmasValue<-SumOfSigmasValue+value + } + SumOfSigmaAAs[i]<-SumOfSigmasValue +} + +# AAs1<-length(substrates[,1])-sum(substrates[,1]=="") +# AAs2<-length(substrates[,2])-sum(substrates[,2]=="") +# AAs3<-length(substrates[,3])-sum(substrates[,3]=="") +# AAs4<-length(substrates[,4])-sum(substrates[,4]=="") +# AAs5<-length(substrates[,5])-sum(substrates[,5]=="") +# AAs6<-length(substrates[,6])-sum(substrates[,6]=="") +# AAs7<-length(substrates[,7])-sum(substrates[,7]=="") +# AAs8<-length(substrates[,8])-sum(substrates[,8]=="") +# AAs9<-length(substrates[,9])-sum(substrates[,9]=="") +# #AAsAtPositions<-c(AAs1,AAs2,AAs3,AAs4,AAs5,AAs6,AAs7,AAs8,AAs9) +# AAsAtPositions<-c(length(substrates[,1]),length(substrates[,2]),length(substrates[,3]),length(substrates[,4]), +# length(substrates[,5]),length(substrates[,6]),length(substrates[,7]),length(substrates[,8]), +# length(substrates[,9])) + + +# SumOfExpectedSigmaAAs<-c(1:9) +# for (i in 1:15){ +# ExpectedValue<-0 +# for (j in 1:20){ +# value<-0 +# if (bareSDs[j,i]>1){ +# value<-AllMeans[j] +# } +# ExpectedValue<-ExpectedValue+value +# } +# SumOfExpectedSigmaAAs[i]<-ExpectedValue*(length(substrates[,i])-sum(substrates[,i]%in% ""))/100 +# } +# +# SelectivityRow<-SumOfSigmaAAs/SumOfExpectedSigmaAAs +# SuperRow<-SelectivityRow + + +#90% whatevernness +# TPninetyone<-length(PositiveWeirdScores[PositiveWeirdScores>=0.91]) +# Senseninetyone<-TPninetyone/nrow(positivesubstrates) +# +# TNninetyone<-length(NegativeWeirdScores[NegativeWeirdScores<91]) +# Specninetyone<-TNninetyone/100 + +#create the MCC table + +threshold<-c(1:100,(1:9)/10,(1:9)/100,0,-.1) +threshold<-threshold[order(threshold,decreasing = TRUE)] +threshold + +Truepositives<-c(1:120) +Falsenegatives<-c(1:120) +Sensitivity<-c(1:120) +TrueNegatives<-c(1:120) +FalsePositives<-c(1:120) +One_Minus_Specificity<-c(1:120) +Accuracy<-c(1:120) +MCC<-c(1:120) +EER<-c(1:120) +Precision<-c(1:120) +F_One_Half<-c(1:120) +F_One<-c(1:120) +F_Two<-c(1:120) +FalsePositiveRate<-c(1:120) +#MAKE DAMN SURE THAT THE ACCESSION NUMBERS FOLLOW THE MOTIFS + +for (z in 1:120) { + thres<-threshold[z] + Truepositives[z]<-length(PositiveWeirdScores[PositiveWeirdScores>=(thres)]) + Falsenegatives[z]<-nrow(positivesubstrates)-Truepositives[z] + Sensitivity[z]<-Truepositives[z]/(Falsenegatives[z]+Truepositives[z]) + TrueNegatives[z]<-length(NegativeWeirdScores[NegativeWeirdScores<(thres)]) + # at thresh 100 this should be 0, because it is total minus true negatives + FalsePositives[z]<-nrow(NegativeSubstrateList)-TrueNegatives[z] + One_Minus_Specificity[z]<-1-(TrueNegatives[z]/(FalsePositives[z]+TrueNegatives[z])) + Accuracy[z]<-100*(Truepositives[z]+TrueNegatives[z])/(Falsenegatives[z]+FalsePositives[z]+TrueNegatives[z]+Truepositives[z]) + MCC[z]<-((Truepositives[z]*TrueNegatives[z])-(Falsenegatives[z]*FalsePositives[z]))/sqrt(round(round(Truepositives[z]+Falsenegatives[z])*round(TrueNegatives[z]+FalsePositives[z])*round(Truepositives[z]+FalsePositives[z])*round(TrueNegatives[z]+Falsenegatives[z]))) + #EER[z]<-.01*(((1-(Sensitivity[z]))*(Truepositives[z]+Falsenegatives[z]))+(Specificity[z]*(1-(Truepositives[z]+Falsenegatives[z])))) + EER[z]<-(FalsePositives[z]+Falsenegatives[z])/(Truepositives[z]+TrueNegatives[z]+FalsePositives[z]+Falsenegatives[z]) + Precision[z]<-Truepositives[z]/(Truepositives[z]+FalsePositives[z]) + F_One_Half[z]<-(1.5*Precision[z]*Sensitivity[z])/(.25*Precision[z]+Sensitivity[z]) + F_One[z]<-(2*Precision[z]*Sensitivity[z])/(Precision[z]+Sensitivity[z]) + F_Two[z]<-(5*Precision[z]*Sensitivity[z])/(4*Precision[z]+Sensitivity[z]) + FalsePositiveRate[z]<-FalsePositives[z]/(TrueNegatives[z]+FalsePositives[z]) +} +Characterization<-cbind.data.frame(threshold,Truepositives,Falsenegatives,Sensitivity,TrueNegatives,FalsePositives,One_Minus_Specificity,Accuracy,MCC,EER,Precision,FalsePositiveRate,F_One_Half,F_One,F_Two) + +positiveheader<-c(1,2,3,4,5,6,7,8,9,10,11,12,13,"RPMS","PMS") +positivewithscores<-rbind.data.frame(positiveheader,positivewithscores) + +negativeheader<-c("Substrate","RPMS","PMS") +colnames(NegativeWithScores)<-negativeheader + +# write.xlsx(NegativeWithScores,file = FILENAME, sheetName = "Negative Sequences Scored",col.names = TRUE,row.names = FALSE,append = TRUE) +# write.xlsx(Characterization,file = FILENAME,sheetName = "Characterization Table",col.names = TRUE,row.names = FALSE,append = TRUE) +# write.xlsx(RanksPeptides,file = FILENAME,sheetName = "Ranked Generated Peptides",col.names = FALSE,row.names = FALSE,append = TRUE) +# write.xlsx(positivewithscores,file = FILENAME, sheetName = "Positive Sequences Scored",col.names = FALSE,row.names = FALSE,append = TRUE) +write.table(x=c("Characterzation Table"),file = FILENAME2, col.names = FALSE,row.names = FALSE, append = TRUE,sep = ",") +write.table(Characterization,file = FILENAME2, col.names = TRUE,row.names = FALSE, append = TRUE,sep = ",") + + +#write.table(RanksPeptides,file = FILENAME3,append = TRUE,row.names = FALSE,col.names = TRUE,sep = ",") + + +options(warn = oldw)
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/KT-ID fisher test/kinatestid_r_fisher.xml Mon Jan 14 11:12:59 2019 -0500 @@ -0,0 +1,47 @@ +<tool id="kinatestid_fisher_r" name="Kinatest-ID using Fisher's Exact Test" version="0.5.0"> + <description>determine kinase's preferred sequence motif</description> + <requirements> + <requirement type="package">R</requirement> + </requirements> + <command><![CDATA[ + ln -s '$substrates' substrates.csv && + ln -s '$negatives' negatives.csv && + ln -s '$SBF' SBF.csv && + ln -s '$__tool_directory__/screener7-7.csv' screener && + ln -s '$__tool_directory__/OnlyTheRequiredSubBackFreqData.RData' thedata.RData && + Rscript '$__tool_directory__/7-7-fisher-galaxy_working.R' + ]]></command> + <inputs> + <param format="csv" name="substrates" type="data" label="Positive/Phosphorylated Substrate List"/> + <param format="csv" name="negatives" type="data" label="Negative/unPhosphorylated Substrate List"/> + <param format="csv" name="SBF" type="data" label="Substrate Background Frequency List"/> + <param name="outGroup" type="text" value="kinase" label="Kinase Name"/> + </inputs> + <outputs> + <data format="csv" name="odds_table" from_work_dir="output1.csv" label="${outGroup}_Fisher Odds Table"/> + <data format="csv" name="char_table" from_work_dir="output2.csv" label="${outGroup}_Characterization Table"/> + </outputs> + <tests> + <test> + <param name="substrates" ftype="csv" value="substrates.csv"/> + <param name="negatives" ftype="csv" value="negatives.csv"/> + <param name="SBF" ftype="csv" value="SBF.csv"/> + <output name="SDtable" file="SDtable.csv"/> + <output name="EPM" file="EPM.csv"/> + <output name="Characterization" file="Characterization.csv"/> + </test> + </tests> + + + <help><![CDATA[ + + +This tool is intended for use in conjunction with a Kinamine tool and a Negative Motif Finder tool. Using the outputs from those two functions (The Positive and Negative substrates as well as the Substrate Background Frequency) this tool calculates the kinases preferred substrate motif. + + + ]]></help> + <citations> + <citation type="doi">10.1074/mcp.RA118.001111</citation> + </citations> +</tool> +
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