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Copy pathSupplementary Code_DIADataAnalyzer.R
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Supplementary Code_DIADataAnalyzer.R
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#######01. Build the mixed library;
BML<-function(MSMSFileName="msms.txt",EvidenceFileName="evidence.txt",LibraryFileName,
charge="no",RTShift=5,Scorediff=0,Lprob=0,Class="none"){
###store the names
datamsms1<-read.table(MSMSFileName,header=T,check.names =F,stringsAsFactors=F,sep="\t")
datamsms_name1<-names(datamsms1)
###
datamsms<-read.table(MSMSFileName,header=T,stringsAsFactors=F,sep="\t")
datamsms_name<-names(datamsms)
data_evi<-read.table(EvidenceFileName,head=T,stringsAsFactors=F,sep="\t")
#####filter msms.txt
contamin_evi<-which(data_evi$Potential.contaminant=="+")
contamin_pep<-unique(c(data_evi$Modified.sequence[contamin_evi]))
ncontamin_pep<-length(contamin_pep)
contamin_msms<-vector()
for(ic in 1:ncontamin_pep){
contamin_msms1<-which(datamsms$Modified.sequence==contamin_pep[ic])
contamin_msms[ic]<-paste(contamin_msms1,collapse=";")
}
contamin_msms_total1<-paste(contamin_msms,collapse=";")
contamin_msms_total<-strsplit(contamin_msms_total1,";")
contamin_msms_total_num<-unique(c(as.numeric(contamin_msms_total[[1]])))
ph_num<-which(datamsms$Phospho..STY.==0)
reverse_num<-which(datamsms$Reverse=="+")
num<-unique(c(ph_num,reverse_num,contamin_msms_total_num))
newdatamsms_one<-datamsms[-num,]
if(Class=="Class1"){
score_diff_num<-which(newdatamsms_one$Score.diff>=5)
lprob_num<-which(newdatamsms_one$Localization.prob>=0.75)
class_index<-intersect(score_diff_num,lprob_num)
}
if(Class=="Class2"){
score_diff_num<-which(newdatamsms_one$Score.diff<5)
lprob_num<-which(newdatamsms_one$Localization.prob<0.75 & newdatamsms_one$Localization.prob>=0.25)
class_index<-intersect(score_diff_num,lprob_num)
}
if(Class=="Class3"){
score_diff_num<-which(newdatamsms_one$Score.diff<5)
lprob_num<-which(newdatamsms_one$Localization.prob<0.25)
class_index<-intersect(score_diff_num,lprob_num)
}
if(Class=="none"){
score_diff_num<-which(newdatamsms_one$Score.diff>=Scorediff)
lprob_num<-which(newdatamsms_one$Localization.prob>=Lprob)
class_index<-intersect(score_diff_num,lprob_num)
}
newdatamsms<-newdatamsms_one[class_index,]
modi_num<-which(datamsms_name=="Modified.sequence")
newdatamsms<-newdatamsms[order(newdatamsms[,modi_num]),]
#####Get the mixed library
newdatamsms01<-newdatamsms
if(charge=="yes"){
newmodseq_charge<-paste(newdatamsms01$Modified.sequence,newdatamsms01$Charge,sep="-")
}else{
newmodseq_charge<-newdatamsms01$Modified.sequence
}
tabledata<-table(newmodseq_charge)
n<-length(tabledata)
rownum01<-vector()
pb<-txtProgressBar(min=1,max=n,char="=>")
for(i in 1:n){
pms<-dimnames(tabledata)[[1]][i]
pms_index<-which(newmodseq_charge==pms)
npms_index<-length(pms_index)
frt1<-vector()
lrt<-1
for(j in 1:npms_index){
frt1[lrt]<-newdatamsms01$Retention.time[pms_index[j]]
lrt<-lrt+1
}
rt_median1<-median(frt1)
newfrt1<-abs(frt1-rt_median1)
newfrt1_index<-which(newfrt1<=RTShift)
newfrt<-frt1[newfrt1_index]
newpms_index<-pms_index[newfrt1_index]
nnewpms_index<-length(newpms_index)
if(nnewpms_index>0){
rownum01[i]<-newpms_index[1]
fion<-vector()
fintensity<-vector()
fionmass<-vector()
l<-1
for(j in 1:nnewpms_index){
fion[l]<-newdatamsms01$Matches[newpms_index[j]]
fintensity[l]<-newdatamsms01$Intensities[newpms_index[j]]
fionmass[l]<-newdatamsms01$Masses[newpms_index[j]]
l<-l+1
}
newdatamsms01$Retention.time[newpms_index[1]]<-median(newfrt)
ms_match<-paste(fion,collapse=";")
ms_intensity<-paste(fintensity,collapse=";")
ms_mass<-paste(fionmass,collapse=";")
newms_match<-strsplit(ms_match,";")
newms_intensity<-strsplit(ms_intensity,";")
newms_mass<-strsplit(ms_mass,";")
new_match_uni<-unique(c(newms_match[[1]]))
newms_intensity_num<-as.numeric(newms_intensity[[1]])
newms_mass_num<-as.numeric(newms_mass[[1]])
nnew_match_uni<-length(new_match_uni)
char_match_uni<-paste(new_match_uni,collapse=";")
which_intensity<-vector()
which_mass<-vector()
for(k in 1:nnew_match_uni){
which_newmatch<-which(newms_match[[1]]==new_match_uni[k])
which_intensity[k]<-max(newms_intensity_num[which_newmatch])
which_mass[k]<-newms_mass_num[which_newmatch[1]]
}
newdatamsms01$Matches[newpms_index[1]]<-char_match_uni
newdatamsms01$Intensities[newpms_index[1]]<-paste(which_intensity,collapse=";")
newdatamsms01$Masses[newpms_index[1]]<-paste(which_mass,collapse=";")
}else{
rownum01[i]<-NA
}
setTxtProgressBar(pb,i)
}
naomit_rownum01<-na.omit(rownum01)
com_datamsms<-newdatamsms01[naomit_rownum01,]
names(com_datamsms)<-datamsms_name1
write.table(com_datamsms,file=LibraryFileName,sep="\t",row.names = F)
close(pb)
}
########02. Calculate the isolation window according to the density of m/z;
CIW<-function(IsoWindowFileName,LibraryFileName,EvidenceFileName="evidence.txt",
ScanrtMS1mean=0.01,ScanrtMS2mean=0.001,Peakpoints=10,
RTSpan=c(0,120),MZSpan=c(300,1500),RTInterval=120,MZInterval=300){
#####Get the RT length
data_com<-read.table(LibraryFileName,head=T,stringsAsFactors=F,sep="\t")
data_evi<-read.table(EvidenceFileName,head=T,stringsAsFactors=F,sep="\t")
phnum_evi<-which(data_evi$Phospho..STY.==0)
reverse_num_evi<-which(data_evi$Reverse=="+")
contamin_evi<-which(data_evi$Potential.contaminant=="+")
num_evi<-unique(c(phnum_evi,reverse_num_evi,contamin_evi))
newdata_evi<-data_evi[-num_evi,]
n<-length(data_com$m.z)
rtle<-vector()
for(ie in 1:n){
evi_pep1<-which(newdata_evi$Modified.sequence==data_com$Modified.sequence[ie])
if(length(evi_pep1)>0){
rt_evi_pep1<-newdata_evi$Retention.length[evi_pep1]
rtle[ie]<-mean(rt_evi_pep1)
#rtle[ie]<-paste(rt_evi_pep1,collapse=";")
}else{
rtle[ie]<-"0"
}
}
rtle_total1<-paste(rtle,collapse=";")
rtle_total<-strsplit(rtle_total1,";")
rtle_total_num<-as.numeric(rtle_total[[1]])
rtle_total_num_index<-which(rtle_total_num!=0)
rtle_total_num_nozero<-rtle_total_num[rtle_total_num_index]
rt_quan<-mean(rtle_total_num_nozero)
#####
#####calculate circle
npeakp<-Peakpoints
circle_time<-rt_quan*60/npeakp
circle_scan_num<-round((circle_time-ScanrtMS1mean*60)/(ScanrtMS2mean*60))
#####calculate the window according to library
isow_regulation<-1
nrt<-RTInterval
nmz<-MZInterval
nnrt<-(RTSpan[2]-RTSpan[1])/nrt
nnmz<-(MZSpan[2]-MZSpan[1])/nmz
rt_interval<-vector()
iso_num<-vector()
interval_mz_num<-vector()
interval_rt_num<-vector()
isolationw<-vector()
isow_center<-vector()
for(ii in 1:nnrt){
rt1<-0+(ii-1)*nrt
rt2<-ii*nrt
rt_interval[ii]<-paste(rt1,rt2,sep="_")
rt3_num<-which(data_com$Retention.time>rt1 & data_com$Retention.time<=rt2)
mz_total<-data_com$m.z[rt3_num]
interval_rt_num[ii]<-sum(mz_total<=MZSpan[2])-sum(mz_total<=MZSpan[1])
aver_total<-interval_rt_num[ii]/(MZSpan[2]-MZSpan[1])
if(aver_total>0){
repeat{
seq1<-MZSpan[1]
mz3_num<-vector()
yyiso<-vector()
nmzseq<-vector()
isow_center2<-vector()
isolationw1<-vector()
for(jj in 1:nnmz){
mz2<-MZSpan[1]+jj*nmz
mz3_num[jj]<-sum(mz_total<=mz2)-sum(mz_total<=seq1)
aver_mz3<-mz3_num[jj]/nmz
if(aver_mz3>0){
xx<-aver_total/aver_mz3
yy<-round(exp(xx^(1/sqrt(xx)))+5*xx^3+isow_regulation)
if(yy>nmz){
yy<-nmz
yyiso[jj]<-yy
mzseq<-seq(seq1,mz2,yy)
nmzseq[jj]<-length(mzseq)
seq1<-mzseq[nmzseq[jj]]
}else{
yyiso[jj]<-yy
mzseq<-seq(seq1,mz2,yy)
nmzseq[jj]<-length(mzseq)
seq1<-mzseq[nmzseq[jj]]
}
isow_center1<-mzseq[1:(nmzseq[jj]-1)]+yy/2
isolationw1[jj]<-paste(mzseq,collapse=";")
isow_center2[jj]<-paste(isow_center1,collapse=";")
}else{
yy<-mz2-seq1
yyiso[jj]<-yy
mzseq<-seq(seq1,mz2,yy)
nmzseq[jj]<-length(mzseq)
seq1<-mzseq[nmzseq[jj]]
isow_center1<-mzseq[1:(nmzseq[jj]-1)]+yy/2
isolationw1[jj]<-paste(mzseq,collapse=";")
isow_center2[jj]<-paste(isow_center1,collapse=";")
}
}
isow_regulation<-isow_regulation+1
if((sum(nmzseq)-3)<=circle_scan_num) break
}
iso_num[ii]<-paste(yyiso,collapse=";")
interval_mz_num[ii]<-paste(mz3_num,collapse=";")
isolationw[ii]<-paste(isolationw1,collapse="_")
isow_center[ii]<-paste(isow_center2,collapse="_")
}else{
iso_num[ii]<-"None"
interval_mz_num[ii]<-"None"
isolationw[ii]<-"None"
isow_center[ii]<-"None"
}
}
rt_num<-paste(interval_rt_num,collapse=";")
isodata<-data.frame(RT=rt_interval,RT_Num=rt_num,MZ_Num=interval_mz_num,Isolation_Num=iso_num,
Iso_window=isolationw,Iso_window_center=isow_center)
write.csv(isodata,file=IsoWindowFileName,row.names=F)
}
########03. Deal with the transition results from Skyline
##First, get the total peptide modified sequence that doesn't contain the "precursor";
##Second, extract the peptides whose n(ph) != n(STY)
ETRF<-function(TranFileName,FIonsNumber=3,qvalue=0.01){
tran_result01<-read.csv(TranFileName,header=T,stringsAsFactors=F,sep=",")
remove_NA01<-which(tran_result01$annotation_QValue=="#N/A")
newtran02<-tran_result01[-remove_NA01,]
tran_qvalue<-as.numeric(newtran02$annotation_QValue)
Qvalue01<-which(tran_qvalue<=qvalue)
newtran03<-newtran02[Qvalue01,]
tran_area_index<-which(as.numeric(newtran03$Area)==0)
newtran01<-newtran03[-tran_area_index,]
tran_fion<-newtran01$Fragment.Ion
ntran_fion<-length(tran_fion)
frag_pre01<-vector()
jfpre<-1
for(ifpre in 1:ntran_fion){
grep_frag_pre<-gregexpr("precursor",tran_fion[ifpre])
if(sum(grep_frag_pre[[1]])>0){
frag_pre01[jfpre]<-ifpre
jfpre<-jfpre+1
}
}
newtran<-newtran01[-frag_pre01,]
tabledata<-table(newtran$Peptide.Modified.Sequence)
n<-length(tabledata)
newfname<-vector()
newpname<-vector()
newpms<-vector()
newprecursor_mass<-vector()
newcharge<-vector()
newfion<-vector()
newtran_mass<-vector()
newarea<-vector()
newrt<-vector()
newstime<-vector()
newetime<-vector()
for(i in 1:n){
pms<-dimnames(tabledata)[[1]][i]
pms_index<-which(newtran$Peptide.Modified.Sequence==pms)
pms_fions<-newtran$Fragment.Ion[pms_index]
npms_fions<-length(pms_fions)
pms_fions_new<-unique(pms_fions)
npms_index<-length(pms_fions_new)
pms_index01<-which(newtran01$Peptide.Modified.Sequence==pms)
fion<-vector()
fionmass1<-vector()
fionmass<-vector()
l<-1
if(npms_index>=FIonsNumber){
for(j in 1:npms_fions){
fion[l]<-newtran$Fragment.Ion[pms_index[j]]
fion_charge<-newtran$Product.Charge[pms_index[j]]
fionmass1[l]<-newtran$Product.Mz[pms_index[j]]*fion_charge-(fion_charge-1)*1.0079
l<-l+1
}
fionuni<-unique(fion)
nfionuni<-length(fionuni)
for(ifionuni in 1:nfionuni){
which_fionuni<-which(fion==fionuni[ifionuni])
fionmass[ifionuni]<-fionmass1[which_fionuni[1]]
}
}else{
fionuni<-NA
fionmass[l]<-NA
}
newfname[i]<-newtran$File.Name[pms_index[1]]
newpname[i]<-newtran$Protein.Name[pms_index[1]]
newpms[i]<-pms
newprecursor_mass[i]<-newtran01$Product.Mz[pms_index01[1]]
newcharge[i]<-newtran01$Product.Charge[pms_index01[1]]
newfion[i]<-paste(fionuni,collapse=";")
newtran_mass[i]<-paste(fionmass,collapse=";")
newarea[i]<-newtran01$Total.Area.MS1[pms_index01[1]]
newrt[i]<-newtran$Peptide.Retention.Time[pms_index[1]]
newstime[i]<-newtran$Min.Start.Time[pms_index[1]]
newetime[i]<-newtran$Max.End.Time[pms_index[1]]
}
newfion_NA<-which(newfion=="NA")
newmsmstxt1<-data.frame(File_Name=newfname,Protein_Name=newpname,Peptide_Modified_Sequence=newpms,
Precursor_Mass=newprecursor_mass,Precursor_Charge=newcharge,Fragment_Ions=newfion,FIMasses=newtran_mass,
Area=newarea,Rentention_Time=newrt,Start_Time=newstime,End_Time=newetime)
if(length(newfion_NA)==0){
newmsmstxt<-newmsmstxt1
}else{
newmsmstxt<-newmsmstxt1[-newfion_NA,]
}
totfname<-paste("Outtotal_",TranFileName,sep="")
write.csv(newmsmstxt,row.names=F,file=totfname)
modseq<-as.character(newmsmstxt$Peptide_Modified_Sequence)
modseq<-gsub("\\[\\+42\\]","a",modseq)
modseq<-gsub("\\[\\+80\\]","p",modseq)
modseq<-gsub("\\[\\+16\\]","o",modseq)
modseq<-gsub("\\[\\+57\\]","c",modseq)
modseq<-gsub("\\[\\+10\\]","r",modseq)
modseq<-gsub("\\[\\+8\\]","l",modseq)
modseq<-gsub("\\[.+?\\]","",modseq)
modseqph<-gsub("a|o|c|l|r","",modseq)
nomodseq<-gsub("a|o|c|p|l|r","",modseq)
length_modseq<-length(newmsmstxt$Peptide_Modified_Sequence)
nphsty<-vector()
jj<-1
for(i in 1:length_modseq){
char_modseq_ph<-gregexpr("p",modseqph[i])
nseqph<-sum(char_modseq_ph[[1]]>=1)
char_sty<-gregexpr("S|T|Y",nomodseq[i])
nchar_sty<-length(char_sty[[1]])
no_ms_split<-strsplit(nomodseq[i],"")
nby<-length(no_ms_split[[1]])
char_frag_ion<-as.character(newmsmstxt$Fragment_Ions[i])
fragion<-strsplit(char_frag_ion,";")
if(nseqph==nchar_sty){
nphsty[jj]<-i
jj<-jj+1
}
}
if(length(nphsty)>0){
data_phsty<-newmsmstxt[-nphsty,]
}else{
data_phsty<-newmsmstxt
}
data_phsty_normal<-newmsmstxt[unique(nphsty),]
normalfn<-paste("Normal_",TranFileName,sep="") #n(ph) = n(STY)
write.csv(data_phsty_normal,row.names=F,file=normalfn)
target_fn<-paste("Target_",TranFileName,sep="") #n(ph) != n(STY)
write.csv(data_phsty,row.names=F,file=target_fn)
}
######04. Get the probable peptides list and sum the high XCorr of each ion
GPPL_Target<-function(TargetFileName,RawFileName,IsoWindowFileName,
min_num_fragion,CorThreshold,aboveCor,
ppt,peakTolThreshold){
data_phsty_proba<-read.csv(TargetFileName,head=T,stringsAsFactors=F,sep=",")
modseq1_first<-as.character(data_phsty_proba$Peptide_Modified_Sequence)
modseq1_first<-gsub("\\[\\+42\\]","a",modseq1_first)
modseq1_first<-gsub("\\[\\+80\\]","p",modseq1_first)
modseq1_first<-gsub("\\[\\+16\\]","o",modseq1_first)
modseq1_first<-gsub("\\[\\+57\\]","c",modseq1_first)
modseq1_first<-gsub("\\[\\+10\\]","r",modseq1_first)
modseq1_first<-gsub("\\[\\+8\\]","l",modseq1_first)
modseq1_first_noph<-gsub("p","",modseq1_first)
nomodseq1_first<-gsub("a|p|o|c|l|r","",modseq1_first)
nmodseq1_first<-length(modseq1_first)
File_Name<-vector()
Protein_Name<-vector()
Peptide_Modified_Sequence<-vector()
Precursor_Mass<-vector()
Precursor_Charge<-vector()
Fragment_Ions<-vector()
FIMasses<-vector()
Rentention_Time<-vector()
Start_Time<-vector()
End_Time<-vector()
Serial_Number_Extension<-vector()
i_combn<-1
pb1<- txtProgressBar(min=1,max=nmodseq1_first,char="=>")
for(i in 1:nmodseq1_first){
newmodseq1_first_split<-strsplit(modseq1_first_noph[i],"")
nnewmodseq1_first<-length(newmodseq1_first_split[[1]])
newmodseq1_first<-vector()
for(i_first_split in 1:nnewmodseq1_first){
if(newmodseq1_first_split[[1]][i_first_split]=="a" | newmodseq1_first_split[[1]][i_first_split]=="p" | newmodseq1_first_split[[1]][i_first_split]=="o"| newmodseq1_first_split[[1]][i_first_split]=="c"){
newmodseq1_first[i_first_split-1]<-paste(newmodseq1_first_split[[1]][i_first_split-1],newmodseq1_first_split[[1]][i_first_split],sep="")
}else{
newmodseq1_first[i_first_split]<-newmodseq1_first_split[[1]][i_first_split]
}
}
newmodseq2_first<-na.omit(newmodseq1_first)
char_nomodseq1_first<-strsplit(nomodseq1_first[i],"")
char_sty<-gregexpr("S|T|Y",nomodseq1_first[i])
nchar_sty<-length(char_sty[[1]])
char_ph<-gregexpr("p",modseq1_first[i])
nchar_ph<-length(char_ph[[1]])
nchoose_sty_ph<-choose(nchar_sty,nchar_ph)
combn_sty_ph<-combinations(nchar_sty,nchar_ph)
for(j in 1:nchoose_sty_ph){
File_Name[i_combn]<-data_phsty_proba$File_Name[i]
Protein_Name[i_combn]<-data_phsty_proba$Protein_Name[i]
Precursor_Mass[i_combn]<-data_phsty_proba$Precursor_Mass[i]
Precursor_Charge[i_combn]<-data_phsty_proba$Precursor_Charge[i]
Fragment_Ions[i_combn]<-data_phsty_proba$Fragment_Ions[i]
FIMasses[i_combn]<-data_phsty_proba$FIMasses[i]
Rentention_Time[i_combn]<-data_phsty_proba$Rentention_Time[i]
Start_Time[i_combn]<-data_phsty_proba$Start_Time[i]
End_Time[i_combn]<-data_phsty_proba$End_Time[i]
Serial_Number_Extension[i_combn]<-i
sty_index<-char_sty[[1]][combn_sty_ph[j,]]
new_sty<-paste(newmodseq2_first[sty_index],"p",sep="")
newmodseq3_first<-newmodseq2_first
newmodseq3_first[sty_index]<-new_sty
new_char_nomodseq1_first<-paste(newmodseq3_first,collapse="")
Peptide_Modified_Sequence[i_combn]<-new_char_nomodseq1_first
i_combn<-i_combn+1
}
setTxtProgressBar(pb1,i)
}
new_seq1_first<-gsub("a","[+42]",Peptide_Modified_Sequence)
new_seq1_first<-gsub("p","[+80]",new_seq1_first)
new_seq1_first<-gsub("o","[+16]",new_seq1_first)
new_seq1_first<-gsub("c","[+57]",new_seq1_first)
new_seq1_first<-gsub("r","[+10]",new_seq1_first)
new_seq1_first<-gsub("l","[+8]",new_seq1_first)
data_phsty<-data.frame(File_Name=File_Name,
Protein_Name=Protein_Name,
Peptide_Modified_Sequence=new_seq1_first,
Precursor_Mass=Precursor_Mass,
Precursor_Charge=Precursor_Charge,
Fragment_Ions=Fragment_Ions,
FIMasses=FIMasses,
Rentention_Time=Rentention_Time,
Start_Time=Start_Time,
End_Time=End_Time,
Serial_Number_Extension=Serial_Number_Extension)
#PSite_NoChange_FileName<-paste("Add_PSite_NoChangedFiMasses_",TargetFileName,sep="")
#write.csv(data_phsty,row.names=F,file=PSite_NoChange_FileName)
close(pb1)
data_rawms2<-read.table(RawFileName,head=T,stringsAsFactors=F,sep="\t")
nrawms2<-length(data_rawms2$ScanNum)
data_isolationw<-read.csv(IsoWindowFileName,head=T,stringsAsFactors=F,sep=",")
ndata_isolationw<-length(data_isolationw[[1]])
niw_times<-nrawms2%/%ndata_isolationw
newdata_isolationw<-rep(data_isolationw$Center,niw_times)
data_isolationw_after<-data.frame(IW_Center=newdata_isolationw) #Isolation Window Center
n_isow<-niw_times*ndata_isolationw
newdata_rawms2<-cbind(data_rawms2[1:n_isow,],data_isolationw_after)
modifiedaa<-hash(Hyd=1.0079,Car=12.0107,Nit=14.0067,Oxi=15.9994,Pho=30.9738,Sul=32.065,
ac=42.01056,ox=15.99491,ph=79.9663,ca=57.0215,ly=8.0142,ar=10.00827,
A=71.03711,R=156.10111,N=114.04293,D=115.02694,C=103.00919,
E=129.04259,Q=128.05858,G=57.02146,H=137.05891,I=113.08406,
L=113.08406,K=128.09496,M=131.04049,F=147.06841,P=97.05276,
S=87.03203,T=101.04768,W=186.07931,Y=163.06333,V=99.06841)
n_data_phsty<-length(data_phsty$Protein_Name)
modseq<-data_phsty$Peptide_Modified_Sequence
modseq<-gsub("\\[\\+42\\]","a",modseq)
modseq<-gsub("\\[\\+80\\]","p",modseq)
modseq<-gsub("\\[\\+16\\]","o",modseq)
modseq<-gsub("\\[\\+57\\]","c",modseq)
modseq<-gsub("\\[\\+10\\]","r",modseq)
modseq<-gsub("\\[\\+8\\]","l",modseq)
modseq_ac<-gsub("p|o|c|r|l","",modseq)
modseq_ph<-gsub("a|o|c|r|l","",modseq)
modseq_ox<-gsub("a|p|c|r|l","",modseq)
modseq_ca<-gsub("a|p|o|r|l","",modseq)
modseq_ar<-gsub("a|p|o|l|c","",modseq)
modseq_ly<-gsub("a|p|o|c|r","",modseq)
nomodseq<-gsub("a|o|c|p|r|l","",modseq)
pb2<-txtProgressBar(min=1,max=n_data_phsty,char="=>")
spe_ref_XCorr_total_sum<-vector()
spe_ref_XCorr_total_sum_filter<-vector()
#found_frigmentions_sum_intensity<-vector()
#found_frigmentions_sum_intensity_filter<-vector()
found_frigmentions_sum_intensity_log<-vector()
found_frigmentions_sum_intensity_log_filter<-vector()
found_frigmentions_sum_intensity_total_filter<-vector()
Number_FragIons_Total<-vector()
number_FragIons_aboveCorthreshold<-vector()
found_frigmentions_sum_intensity_log_filter_average<-vector()
#WeightedCorr_total_average<-vector()
j_proba<-1
for(i_proba in 1:n_data_phsty){
iw_compare1<-abs(data_phsty$Precursor_Mass[i_proba]-data_isolationw$Center[1:(ndata_isolationw/2)])
iw_compare_index1<-which.min(iw_compare1)
sub_ms2_iw_center_precursor1<-data_isolationw$Center[1:(ndata_isolationw/2)][iw_compare_index1]
iw_compare2<-abs(data_phsty$Precursor_Mass[i_proba]-data_isolationw$Center[(ndata_isolationw/2+1):ndata_isolationw])
iw_compare_index2<-which.min(iw_compare2)
sub_ms2_iw_center_precursor2<-data_isolationw$Center[(ndata_isolationw/2+1):ndata_isolationw][iw_compare_index2]
#for(jisow in 1:ndata_isolationw){
#if(data_phsty$Precursor_Mass[i_proba]<data_isolationw$End[jisow] & data_phsty$Precursor_Mass[i_proba]>=data_isolationw$Start[jisow]){
#sub_ms2_iw_center_precursor<-data_isolationw$Center[jisow]
#break
#}
#}
iw_each_index<-vector()
iw_each_index1<-which(newdata_rawms2$IW_Center==sub_ms2_iw_center_precursor1)
iw_each_index2<-which(newdata_rawms2$IW_Center==sub_ms2_iw_center_precursor2)
jw<-1
for(iw in 1:length(iw_each_index1)){
iw_each_index[jw]<-iw_each_index1[iw]
iw_each_index[jw+1]<-iw_each_index2[iw]
jw<-jw+2
}
iw_each<-newdata_rawms2[iw_each_index,]
datapsm01<-iw_each
####
bmass<-vector()
ymass<-vector()
noms_split<-strsplit(nomodseq[i_proba],"")
nnoms_split<-length(noms_split[[1]])
bmass[1]<-modifiedaa[[noms_split[[1]][1]]]+modifiedaa$Hyd
bb<-bmass[1]
ymass[1]<-modifiedaa[[noms_split[[1]][nnoms_split]]]+modifiedaa$Hyd*3+modifiedaa$Oxi
yy<-ymass[1]
for(jb in 2:nnoms_split){
bb<-bb+modifiedaa[[noms_split[[1]][jb]]]
bmass[jb]<-bb
}
for(jy in 2:nnoms_split){
yy<-yy+modifiedaa[[noms_split[[1]][nnoms_split-jy+1]]]
ymass[jy]<-yy
}
newbmass<-bmass
newymass<-ymass
nby<-nnoms_split
char_modseq_ac<-gregexpr("a",modseq_ac[i_proba])
char_modseq_ox<-gregexpr("o",modseq_ox[i_proba])
char_modseq_ph<-gregexpr("p",modseq_ph[i_proba])
char_modseq_ca<-gregexpr("c",modseq_ca[i_proba])
char_modseq_ar<-gregexpr("r",modseq_ar[i_proba])
char_modseq_ly<-gregexpr("l",modseq_ly[i_proba])
nseq_ac<-sum(char_modseq_ac[[1]]>=1)
nseq_ox<-sum(char_modseq_ox[[1]]>=1)
nseq_ph<-sum(char_modseq_ph[[1]]>=1)
nseq_ca<-sum(char_modseq_ca[[1]]>=1)
nseq_ar<-sum(char_modseq_ar[[1]]>=1)
nseq_ly<-sum(char_modseq_ly[[1]]>=1)
if(nseq_ac>=1){
for(acj in 1:nseq_ac){
nacj<-char_modseq_ac[[1]][acj]-acj
newbmass[nacj:nby]<-newbmass[nacj:nby]+modifiedaa$ac
newymass[(nby-nacj+1):nby]<-newymass[(nby-nacj+1):nby]+modifiedaa$ac
}
}
if(nseq_ox>=1){
for(oxj in 1:nseq_ox){
noxj<-char_modseq_ox[[1]][oxj]-oxj
newbmass[noxj:nby]<-newbmass[noxj:nby]+modifiedaa$ox
newymass[(nby-noxj+1):nby]<-newymass[(nby-noxj+1):nby]+modifiedaa$ox
}
}
if(nseq_ca>=1){
for(caj in 1:nseq_ca){
ncaj<-char_modseq_ca[[1]][caj]-caj
newbmass[ncaj:nby]<-newbmass[ncaj:nby]+modifiedaa$ca
newymass[(nby-ncaj+1):nby]<-newymass[(nby-ncaj+1):nby]+modifiedaa$ca
}
}
if(nseq_ph>=1){
for(phj in 1:nseq_ph){
nphj<-char_modseq_ph[[1]][phj]-phj
newbmass[nphj:nby]<-newbmass[nphj:nby]+modifiedaa$ph
newymass[(nby-nphj+1):nby]<-newymass[(nby-nphj+1):nby]+modifiedaa$ph
}
}
if(nseq_ar>=1){
for(arj in 1:nseq_ar){
narj<-char_modseq_ar[[1]][arj]-arj
newbmass[narj:nby]<-newbmass[narj:nby]+modifiedaa$ar
newymass[(nby-narj+1):nby]<-newymass[(nby-narj+1):nby]+modifiedaa$ar
}
}
if(nseq_ly>=1){
for(lyj in 1:nseq_ly){
nlyj<-char_modseq_ly[[1]][lyj]-lyj
newbmass[nlyj:nby]<-newbmass[nlyj:nby]+modifiedaa$ly
newymass[(nby-nlyj+1):nby]<-newymass[(nby-nlyj+1):nby]+modifiedaa$ly
}
}
newymass<-newymass-0.005
yyrev<-rev(newymass)
#### not start from the first ion
blabel1<-paste(c("b"),1:nby,sep="")
blabel2<-paste(blabel1," -H2O",sep="")
blabel3<-paste(blabel1," -NH3",sep="")
blabel4<-paste(blabel1," -98",sep="")
ylabel1<-paste(c("y"),1:nby,sep="")
ylabel2<-paste(ylabel1," -H2O",sep="")
ylabel3<-paste(ylabel1," -NH3",sep="")
ylabel4<-paste(ylabel1," -98",sep="")
####Obtain the decoy sequence fragment ions masses with the same b-y labels of target peptide;
fiby_label<-c(blabel1,blabel2,blabel3,blabel4,ylabel1,ylabel2,ylabel3,ylabel4)
newbmass_razor<-newbmass[1:nby]
newymass_razor<-newymass[1:nby]
fibymass<-c(newbmass_razor,newbmass_razor-18.0152,newbmass_razor-17.0304,newbmass_razor-97.9815,
newymass_razor,newymass_razor-18.0152,newymass_razor-17.0304,newymass_razor-97.9815)
stime<-as.numeric(as.character(data_phsty$Start_Time[i_proba]))
etime<-as.numeric(as.character(data_phsty$End_Time[i_proba]))
newrt<-which(datapsm01$RT<=etime & datapsm01$RT>=stime)
nnewrt<-length(newrt)
char_sty<-gregexpr("S|T|Y",nomodseq[i_proba])
nchar_sty<-length(char_sty[[1]])
char_fi_mass<-as.character(data_phsty$FIMasses[i_proba])
fimass_char<-strsplit(char_fi_mass,";")
fimass<-as.numeric(fimass_char[[1]])
nfimass<-length(fimass)
fibymass_total<-c(fimass,fibymass)
n_fibymass_total<-length(fibymass_total)
fimass_ph1_intensity_proba<-vector()
str_fi_intensity_proba<-vector()
fimass_ph1_noise_proba<-vector()
str_fi_noise_proba<-vector()
for(sfi1_proba in 1:n_fibymass_total){
for(nrt_proba in 1:nnewrt){
nrt1_proba<-newrt[nrt_proba]
char_mz_proba<-as.character(datapsm01$m.z[nrt1_proba])
str_mz_proba<-strsplit(char_mz_proba,";")
newstr_mz_proba<-as.numeric(str_mz_proba[[1]])
char_intensity_proba<-as.character(datapsm01$Intensity[nrt1_proba])
str_intensity_proba<-strsplit(char_intensity_proba,";")
newstr_intensity_proba<-as.numeric(str_intensity_proba[[1]])
char_noise_proba<-as.character(datapsm01$Noise[nrt1_proba])
str_noise_proba<-strsplit(char_noise_proba,";")
newstr_noise_proba<-as.numeric(str_noise_proba[[1]])
sub_fion1_proba<-abs(newstr_mz_proba-fibymass_total[sfi1_proba])
if(min(sub_fion1_proba)<=peakTolThreshold){
sub_fion1_min_proba<-which.min(sub_fion1_proba)
fimass_ph1_intensity_proba[nrt_proba]<-newstr_intensity_proba[sub_fion1_min_proba]
fimass_ph1_noise_proba[nrt_proba]<-newstr_noise_proba[sub_fion1_min_proba]
}else{
fimass_ph1_intensity_proba[nrt_proba]<-0
fimass_ph1_noise_proba[nrt_proba]<-0.0001
}
}
newfimass_ph1_inten_proba<-paste(fimass_ph1_intensity_proba,collapse=";")
str_fi_intensity_proba[sfi1_proba]<-newfimass_ph1_inten_proba
newfimass_ph1_noise_proba<-paste(fimass_ph1_noise_proba,collapse=";")
str_fi_noise_proba[sfi1_proba]<-newfimass_ph1_noise_proba
}
#get the XCorr
spe_ref_XCorr_by_proba<-vector()
found_frigmentions_by_intensity<-vector()
found_frigmentions_by_intensity_log<-vector()
ncor_by_proba<-1
for(npby2 in (nfimass+1):n_fibymass_total){
str_fi_intensitynew2_proba<-strsplit(str_fi_intensity_proba[npby2],";")
str_fi_intensitynew3_proba<-as.numeric(str_fi_intensitynew2_proba[[1]])
nnozero_str_fi_intensitynew3_1_proba<-sum(str_fi_intensitynew3_proba!=0)
str_fi_noisenew2_proba<-strsplit(str_fi_noise_proba[npby2],";")
str_fi_noisenew3_proba<-as.numeric(str_fi_noisenew2_proba[[1]])
if(nnozero_str_fi_intensitynew3_1_proba<ppt){
spe_ref_XCorr_by_proba[ncor_by_proba]<-0
found_frigmentions_by_intensity[ncor_by_proba]<-0
found_frigmentions_by_intensity_log[ncor_by_proba]<-0
}else{
cor_by1_proba<-vector()
sum_str_fi_intensitynew1_proba<-vector()
for(npby1_proba in 1:nfimass){
str_fi_intensitynew_proba<-strsplit(str_fi_intensity_proba[npby1_proba],";")
str_fi_intensitynew1_proba<-as.numeric(str_fi_intensitynew_proba[[1]])
nnozero_str_fi_intensitynew1_proba<-sum(str_fi_intensitynew1_proba!=0)
if(nnozero_str_fi_intensitynew1_proba<ppt){
cor_by1_proba[npby1_proba]<-0
sum_str_fi_intensitynew1_proba[npby1_proba]<-0
}else{
cor_by1_proba[npby1_proba]<-sum(str_fi_intensitynew1_proba*str_fi_intensitynew3_proba)/sqrt(sum(str_fi_intensitynew1_proba^2)*sum(str_fi_intensitynew3_proba^2))
sum_str_fi_intensitynew1_proba[npby1_proba]<-log2(sum(str_fi_intensitynew1_proba))
}
}
if(all(cor_by1_proba==0)){
spe_ref_XCorr_by_proba[ncor_by_proba]<-0
found_frigmentions_by_intensity[ncor_by_proba]<-0
found_frigmentions_by_intensity_log[ncor_by_proba]<-0
}else{
cor_by_proba_weight<-sum(cor_by1_proba*sum_str_fi_intensitynew1_proba)/sum(sum_str_fi_intensitynew1_proba)
cor_by_noise_proba<-str_fi_intensitynew3_proba/str_fi_noisenew3_proba
ncor_by_noise_proba<-sum(cor_by_noise_proba>0)
cor_by_noise_index_proba<-which(cor_by_noise_proba>0)
cor_by_noise_sum_proba<-sum(cor_by_noise_proba[cor_by_noise_index_proba])
spe_ref_XCorr_by_proba[ncor_by_proba]<-cor_by_proba_weight*(1-exp(-(cor_by_noise_sum_proba-ncor_by_noise_proba)))
found_frigmentions_by_intensity_log[ncor_by_proba]<-log2(sum(str_fi_intensitynew3_proba))
found_frigmentions_by_intensity[ncor_by_proba]<-sum(str_fi_intensitynew3_proba)
}
}
ncor_by_proba<-ncor_by_proba+1
}
spe_ref_XCorr_total_sum[i_proba]<-sum(spe_ref_XCorr_by_proba)
spe_ref_XCorr_total_sum_filter[i_proba]<-sum(spe_ref_XCorr_by_proba[which(spe_ref_XCorr_by_proba>=CorThreshold)])
found_frigmentions_sum_intensity_log[i_proba]<-sum(found_frigmentions_by_intensity_log)
found_frigmentions_sum_intensity_log_filter[i_proba]<-sum(found_frigmentions_by_intensity_log[which(spe_ref_XCorr_by_proba>=CorThreshold)])
found_frigmentions_sum_intensity_total_filter[i_proba]<-sum(found_frigmentions_by_intensity[which(spe_ref_XCorr_by_proba>=CorThreshold)])
Number_FragIons_Total[i_proba]<-sum(spe_ref_XCorr_by_proba>0)
number_FragIons_aboveCorthreshold[i_proba]<-sum(spe_ref_XCorr_by_proba>=CorThreshold)
found_frigmentions_sum_intensity_log_filter_average[i_proba]<-sum(found_frigmentions_by_intensity_log[which(spe_ref_XCorr_by_proba>=CorThreshold)])/sum(spe_ref_XCorr_by_proba>=CorThreshold)
#WeightedCorr_total_average[i_proba]<-sum(spe_ref_XCorr_by_proba[which(spe_ref_XCorr_by_proba>=CorThreshold)])/sum(spe_ref_XCorr_by_proba>=CorThreshold)
setTxtProgressBar(pb2,i_proba)
}
data_phsty_after_proba<-cbind(data_phsty,Spe_Ref_XCorr_Total_Sum=spe_ref_XCorr_total_sum,
Spe_Ref_XCorr_Total_Sum_Filter=spe_ref_XCorr_total_sum_filter,
Found_Frigmentions_Sum_Intensity_Log=found_frigmentions_sum_intensity_log,
Found_Frigmentions_Sum_Intensity_Log_Filter=found_frigmentions_sum_intensity_log_filter,
Number_FragIons_Total=Number_FragIons_Total,
Number_FragIons_aboveCorthreshold=number_FragIons_aboveCorthreshold,
Found_Frigmentions_Sum_Intensity_Log_Filter_Average=found_frigmentions_sum_intensity_log_filter_average,
Found_Frigmentions_Sum_Intensity_Total_Filter=found_frigmentions_sum_intensity_total_filter)
PSite_Change_FileName<-paste("Add_PSite_ChangedFiMasses_",TargetFileName,sep="")
write.csv(data_phsty_after_proba,row.names=F,file=PSite_Change_FileName)
close(pb2)
Serial_Number_Extension_table<-table(data_phsty_after_proba$Serial_Number_Extension)
n_SNE_table<-length(Serial_Number_Extension_table)
which_XCorr_max_paste<-vector()
for(i_table in 1:n_SNE_table){
XCorr_max_index<-which(data_phsty_after_proba$Serial_Number_Extension==i_table)
XCorr_max_modpep_index<-which(data_phsty_after_proba$Peptide_Modified_Sequence[XCorr_max_index]==data_phsty_proba$Peptide_Modified_Sequence[i_table])
modpep_WCorr_filter<-data_phsty_after_proba$Spe_Ref_XCorr_Total_Sum_Filter[XCorr_max_index][XCorr_max_modpep_index]
modpep_intensity_average<-data_phsty_after_proba$Found_Frigmentions_Sum_Intensity_Log_Filter_Average[XCorr_max_index][XCorr_max_modpep_index]
XCorr_max_above_index<-which(data_phsty_after_proba$Spe_Ref_XCorr_Total_Sum_Filter[XCorr_max_index]>modpep_WCorr_filter)
if(length(XCorr_max_above_index)==0){
which_XCorr_max_paste[i_table]<-paste(XCorr_max_index[c(XCorr_max_modpep_index)],collapse=";")
}else{
new_XCorr_max_above_largest_index<-XCorr_max_above_index[which.max(data_phsty_after_proba$Spe_Ref_XCorr_Total_Sum_Filter[XCorr_max_index][XCorr_max_above_index])]
substract_XCorr<-data_phsty_after_proba$Spe_Ref_XCorr_Total_Sum_Filter[XCorr_max_index][new_XCorr_max_above_largest_index]-modpep_WCorr_filter
if(substract_XCorr>=aboveCor){
which_XCorr_max_paste[i_table]<-paste(XCorr_max_index[c(new_XCorr_max_above_largest_index,XCorr_max_modpep_index)],collapse=";")
}else{
which_XCorr_max_paste[i_table]<-paste(XCorr_max_index[c(XCorr_max_modpep_index)],collapse=";")
}
#new_XCorr_max_above_largest_index<-XCorr_max_above_index[which.max(data_phsty_after_proba$Spe_Ref_XCorr_Total_Sum_Filter[XCorr_max_index][XCorr_max_above_index])]
#which_XCorr_max_paste[i_table]<-paste(XCorr_max_index[c(new_XCorr_max_above_largest_index,XCorr_max_modpep_index)],collapse=";")
}
}
which_XCorr_max_paste_total<-paste(which_XCorr_max_paste,collapse=";")
which_XCorr_max<-strsplit(which_XCorr_max_paste_total,";")
data_phsty_after_selection<-data_phsty_after_proba[as.numeric(which_XCorr_max[[1]]),]
data_phsty_after_selection_nozero_index<-which(data_phsty_after_selection$Number_FragIons_aboveCorthreshold>=min_num_fragion)
new_data_phsty_after_selection<-data_phsty_after_selection[data_phsty_after_selection_nozero_index,]
PSite_Change_FileName_selection<-paste("Add_PSite_ChangedFiMasses_selection_",TargetFileName,sep="")
write.csv(new_data_phsty_after_selection,row.names=F,file=PSite_Change_FileName_selection)
}
GPPL_Normal<-function(NormalFileName,RawFileName,IsoWindowFileName,
min_num_fragion,CorThreshold,ppt,peakTolThreshold){
data_phsty_proba<-read.csv(NormalFileName,head=T,stringsAsFactors=F,sep=",")
modseq1_first<-as.character(data_phsty_proba$Peptide_Modified_Sequence)
modseq1_first<-gsub("\\[\\+42\\]","a",modseq1_first)
modseq1_first<-gsub("\\[\\+80\\]","p",modseq1_first)
modseq1_first<-gsub("\\[\\+16\\]","o",modseq1_first)
modseq1_first<-gsub("\\[\\+57\\]","c",modseq1_first)
modseq1_first<-gsub("\\[\\+10\\]","r",modseq1_first)
modseq1_first<-gsub("\\[\\+8\\]","l",modseq1_first)
modseq1_first_noph<-gsub("p","",modseq1_first)
nomodseq1_first<-gsub("a|p|o|c|r|l","",modseq1_first)
nmodseq1_first<-length(modseq1_first)
File_Name<-vector()
Protein_Name<-vector()
Peptide_Modified_Sequence<-vector()
Precursor_Mass<-vector()
Precursor_Charge<-vector()
Fragment_Ions<-vector()
FIMasses<-vector()
Rentention_Time<-vector()
Start_Time<-vector()
End_Time<-vector()
Serial_Number_Extension<-vector()
i_combn<-1
for(i in 1:nmodseq1_first){
newmodseq1_first_split<-strsplit(modseq1_first_noph[i],"")
nnewmodseq1_first<-length(newmodseq1_first_split[[1]])
newmodseq1_first<-vector()
for(i_first_split in 1:nnewmodseq1_first){
if(newmodseq1_first_split[[1]][i_first_split]=="a" | newmodseq1_first_split[[1]][i_first_split]=="p" | newmodseq1_first_split[[1]][i_first_split]=="o"| newmodseq1_first_split[[1]][i_first_split]=="c"){
newmodseq1_first[i_first_split-1]<-paste(newmodseq1_first_split[[1]][i_first_split-1],newmodseq1_first_split[[1]][i_first_split],sep="")
}else{
newmodseq1_first[i_first_split]<-newmodseq1_first_split[[1]][i_first_split]
}
}
newmodseq2_first<-na.omit(newmodseq1_first)
char_nomodseq1_first<-strsplit(nomodseq1_first[i],"")
char_sty<-gregexpr("S|T|Y",nomodseq1_first[i])
nchar_sty<-length(char_sty[[1]])
char_ph<-gregexpr("p",modseq1_first[i])
nchar_ph<-length(char_ph[[1]])
nchoose_sty_ph<-choose(nchar_sty,nchar_ph)
combn_sty_ph<-combinations(nchar_sty,nchar_ph)
for(j in 1:nchoose_sty_ph){
File_Name[i_combn]<-data_phsty_proba$File_Name[i]
Protein_Name[i_combn]<-data_phsty_proba$Protein_Name[i]
Precursor_Mass[i_combn]<-data_phsty_proba$Precursor_Mass[i]
Precursor_Charge[i_combn]<-data_phsty_proba$Precursor_Charge[i]
Fragment_Ions[i_combn]<-data_phsty_proba$Fragment_Ions[i]
FIMasses[i_combn]<-data_phsty_proba$FIMasses[i]
Rentention_Time[i_combn]<-data_phsty_proba$Rentention_Time[i]
Start_Time[i_combn]<-data_phsty_proba$Start_Time[i]
End_Time[i_combn]<-data_phsty_proba$End_Time[i]
Serial_Number_Extension[i_combn]<-i
sty_index<-char_sty[[1]][combn_sty_ph[j,]]
new_sty<-paste(newmodseq2_first[sty_index],"p",sep="")
newmodseq3_first<-newmodseq2_first
newmodseq3_first[sty_index]<-new_sty
new_char_nomodseq1_first<-paste(newmodseq3_first,collapse="")
Peptide_Modified_Sequence[i_combn]<-new_char_nomodseq1_first
i_combn<-i_combn+1
}
}
new_seq1_first<-gsub("a","[+42]",Peptide_Modified_Sequence)
new_seq1_first<-gsub("p","[+80]",new_seq1_first)
new_seq1_first<-gsub("o","[+16]",new_seq1_first)
new_seq1_first<-gsub("c","[+57]",new_seq1_first)
new_seq1_first<-gsub("r","[+10]",new_seq1_first)
new_seq1_first<-gsub("l","[+8]",new_seq1_first)
data_phsty<-data.frame(File_Name=File_Name,
Protein_Name=Protein_Name,
Peptide_Modified_Sequence=new_seq1_first,
Precursor_Mass=Precursor_Mass,
Precursor_Charge=Precursor_Charge,
Fragment_Ions=Fragment_Ions,
FIMasses=FIMasses,
Rentention_Time=Rentention_Time,
Start_Time=Start_Time,
End_Time=End_Time,
Serial_Number_Extension=Serial_Number_Extension)
#PSite_NoChange_FileName<-paste("Add_PSite_NoChangedFiMasses_",TargetFileName,sep="")
#write.csv(data_phsty,row.names=F,file=PSite_NoChange_FileName)
data_rawms2<-read.table(RawFileName,head=T,stringsAsFactors=F,sep="\t")
nrawms2<-length(data_rawms2$ScanNum)
data_isolationw<-read.csv(IsoWindowFileName,head=T,stringsAsFactors=F,sep=",")
ndata_isolationw<-length(data_isolationw[[1]])
niw_times<-nrawms2%/%ndata_isolationw
newdata_isolationw<-rep(data_isolationw$Center,niw_times)
data_isolationw_after<-data.frame(IW_Center=newdata_isolationw) #Isolation Window Center
n_isow<-niw_times*ndata_isolationw
newdata_rawms2<-cbind(data_rawms2[1:n_isow,],data_isolationw_after)
modifiedaa<-hash(Hyd=1.0079,Car=12.0107,Nit=14.0067,Oxi=15.9994,Pho=30.9738,Sul=32.065,
ac=42.01056,ox=15.99491,ph=79.9663,ca=57.0215,ly=8.0142,ar=10.00827,
A=71.03711,R=156.10111,N=114.04293,D=115.02694,C=103.00919,
E=129.04259,Q=128.05858,G=57.02146,H=137.05891,I=113.08406,
L=113.08406,K=128.09496,M=131.04049,F=147.06841,P=97.05276,
S=87.03203,T=101.04768,W=186.07931,Y=163.06333,V=99.06841)
n_data_phsty<-length(data_phsty$Protein_Name)
modseq<-data_phsty$Peptide_Modified_Sequence
modseq<-gsub("\\[\\+42\\]","a",modseq)
modseq<-gsub("\\[\\+80\\]","p",modseq)
modseq<-gsub("\\[\\+16\\]","o",modseq)
modseq<-gsub("\\[\\+57\\]","c",modseq)
modseq<-gsub("\\[\\+10\\]","r",modseq)
modseq<-gsub("\\[\\+8\\]","l",modseq)
modseq_ac<-gsub("p|o|c|r|l","",modseq)
modseq_ph<-gsub("a|o|c|r|l","",modseq)
modseq_ox<-gsub("a|p|c|r|l","",modseq)
modseq_ca<-gsub("a|p|o|r|l","",modseq)
modseq_ar<-gsub("a|p|o|l|c","",modseq)
modseq_ly<-gsub("a|p|o|c|r","",modseq)
nomodseq<-gsub("a|o|c|p|r|l","",modseq)
#pb2<-txtProgressBar(min=1,max=n_data_phsty,char="=>")
spe_ref_XCorr_total_sum<-vector()
spe_ref_XCorr_total_sum_filter<-vector()
#found_frigmentions_sum_intensity<-vector()
#found_frigmentions_sum_intensity_filter<-vector()
found_frigmentions_sum_intensity_log<-vector()
found_frigmentions_sum_intensity_log_filter<-vector()
found_frigmentions_sum_intensity_total_filter<-vector()
Number_FragIons_Total<-vector()
number_FragIons_aboveCorthreshold<-vector()
found_frigmentions_sum_intensity_log_filter_average<-vector()
#WeightedCorr_total_average<-vector()
j_proba<-1
for(i_proba in 1:n_data_phsty){
iw_compare1<-abs(data_phsty$Precursor_Mass[i_proba]-data_isolationw$Center[1:(ndata_isolationw/2)])
iw_compare_index1<-which.min(iw_compare1)
sub_ms2_iw_center_precursor1<-data_isolationw$Center[1:(ndata_isolationw/2)][iw_compare_index1]
iw_compare2<-abs(data_phsty$Precursor_Mass[i_proba]-data_isolationw$Center[(ndata_isolationw/2+1):ndata_isolationw])
iw_compare_index2<-which.min(iw_compare2)
sub_ms2_iw_center_precursor2<-data_isolationw$Center[(ndata_isolationw/2+1):ndata_isolationw][iw_compare_index2]
#for(jisow in 1:ndata_isolationw){
#if(data_phsty$Precursor_Mass[i_proba]<data_isolationw$End[jisow] & data_phsty$Precursor_Mass[i_proba]>=data_isolationw$Start[jisow]){
#sub_ms2_iw_center_precursor<-data_isolationw$Center[jisow]
#break
#}
#}
iw_each_index<-vector()
iw_each_index1<-which(newdata_rawms2$IW_Center==sub_ms2_iw_center_precursor1)
iw_each_index2<-which(newdata_rawms2$IW_Center==sub_ms2_iw_center_precursor2)
jw<-1
for(iw in 1:length(iw_each_index1)){
iw_each_index[jw]<-iw_each_index1[iw]
iw_each_index[jw+1]<-iw_each_index2[iw]
jw<-jw+2
}
iw_each<-newdata_rawms2[iw_each_index,]
datapsm01<-iw_each
####
bmass<-vector()
ymass<-vector()
noms_split<-strsplit(nomodseq[i_proba],"")
nnoms_split<-length(noms_split[[1]])
bmass[1]<-modifiedaa[[noms_split[[1]][1]]]+modifiedaa$Hyd
bb<-bmass[1]
ymass[1]<-modifiedaa[[noms_split[[1]][nnoms_split]]]+modifiedaa$Hyd*3+modifiedaa$Oxi
yy<-ymass[1]
for(jb in 2:nnoms_split){
bb<-bb+modifiedaa[[noms_split[[1]][jb]]]
bmass[jb]<-bb
}
for(jy in 2:nnoms_split){
yy<-yy+modifiedaa[[noms_split[[1]][nnoms_split-jy+1]]]
ymass[jy]<-yy
}
newbmass<-bmass
newymass<-ymass
nby<-nnoms_split
char_modseq_ac<-gregexpr("a",modseq_ac[i_proba])
char_modseq_ox<-gregexpr("o",modseq_ox[i_proba])
char_modseq_ph<-gregexpr("p",modseq_ph[i_proba])
char_modseq_ca<-gregexpr("c",modseq_ca[i_proba])
char_modseq_ar<-gregexpr("r",modseq_ar[i_proba])
char_modseq_ly<-gregexpr("l",modseq_ly[i_proba])
nseq_ac<-sum(char_modseq_ac[[1]]>=1)
nseq_ox<-sum(char_modseq_ox[[1]]>=1)
nseq_ph<-sum(char_modseq_ph[[1]]>=1)
nseq_ca<-sum(char_modseq_ca[[1]]>=1)
nseq_ar<-sum(char_modseq_ar[[1]]>=1)
nseq_ly<-sum(char_modseq_ly[[1]]>=1)
if(nseq_ac>=1){
for(acj in 1:nseq_ac){
nacj<-char_modseq_ac[[1]][acj]-acj
newbmass[nacj:nby]<-newbmass[nacj:nby]+modifiedaa$ac
newymass[(nby-nacj+1):nby]<-newymass[(nby-nacj+1):nby]+modifiedaa$ac
}
}
if(nseq_ox>=1){
for(oxj in 1:nseq_ox){
noxj<-char_modseq_ox[[1]][oxj]-oxj
newbmass[noxj:nby]<-newbmass[noxj:nby]+modifiedaa$ox