R/get_chemscorev1.6.71.R
In yufree/xMSannotator: xMSannotator: R package for network based annotation of metabolomics data.
Defines functions
get_chemscorev1.6.71
get_chemscorev1.6.71 <-
function(chemicalid,mchemicaldata,corthresh,global_cor,mzid,max_diff_rt=10,level_module_isop_annot,
adduct_table,adduct_weights,filter.by=c("M+H"),max_isp=100, MplusH.abundance.ratio.check=TRUE,mass_defect_window=0.01,mass_defect_mode="pos",outlocorig)
{
#new
#print("here")
setwd(outlocorig)
# load("step1_results.Rda")
# load("global_cor.Rda")
outloc1<-paste(outlocorig,"/stage2/",sep="")
suppressWarnings(dir.create(outloc1))
setwd(outloc1)
mchemicaldata$mz<-as.numeric(as.character(mchemicaldata$mz))
mchemicaldata$time<-as.numeric(as.character(mchemicaldata$time))
mchemicaldata$MonoisotopicMass<-as.numeric(as.character(mchemicaldata$MonoisotopicMass))
level_module_isop_annot$mz<-as.numeric(as.character(level_module_isop_annot$mz))
level_module_isop_annot$time<-as.numeric(as.character(level_module_isop_annot$time))
chemical_score<-(-100)
fname<-paste(chemicalid,"data.txt",sep="_")
if(length(mchemicaldata$mz)>0){
if(length(which(duplicated(mchemicaldata$mz)==TRUE))>0){
# mchemicaldata<-mchemicaldata[-which(duplicated(mchemicaldata$mz)==TRUE),]
}
mchemicaldata$Module_RTclust<-gsub(mchemicaldata$Module_RTclust,pattern="_[0-9]*",replacement="")
mchemicaldata_orig<-mchemicaldata
#if(FALSE)
{
if(length(which(mchemicaldata_orig$Adduct%in%as.character(adduct_weights[,1])))>0){
rel_adduct_data<-mchemicaldata[which(mchemicaldata$Adduct%in%as.character(adduct_weights[,1])),]
rel_adduct_module<-gsub(rel_adduct_data$Module_RTclust,pattern="_[0-9]*",replacement="")
module_rt_group<-gsub(mchemicaldata$Module_RTclust,pattern="_[0-9]*",replacement="")
mchemicaldata<-mchemicaldata[which(module_rt_group%in%rel_adduct_module),]
}
}
mchemicaldata<-unique(mchemicaldata)
curformula<-as.character(mchemicaldata[,7])
formula_check<-getMolecule(as.character(curformula[1]))
exp_isp<-which(formula_check$isotopes[[1]][2,]>=0.001)
#print(formula_check)
#print(exp_isp)
abund_ratio_vec<-formula_check$isotopes[[1]][2,exp_isp]
numoxygen<-check_element(curformula,"O")
water_adducts<-c("M+H-H2O","M+H-2H2O","M-H2O-H")
water_adduct_ind<-which(mchemicaldata$Adduct%in%water_adducts)
if(numoxygen<1){
if(length(water_adduct_ind)>0){
mchemicaldata<-mchemicaldata[-water_adduct_ind,]
}
}
#water check
if(nrow(mchemicaldata)<1){
chemical_score<-(-100)
return(list("chemical_score"=chemical_score,"filtdata"=mchemicaldata))
}
mchemicaldata$Adduct<-as.character(mchemicaldata$Adduct)
uniq_adducts<-unique(mchemicaldata$Adduct)
good_adducts<-uniq_adducts[which(uniq_adducts%in%as.character(adduct_weights[,1]))]
table_mod<-table(mchemicaldata$Module_RTclust)
table_iso<-table(mchemicaldata$ISgroup)
table_mod<-table_mod[table_mod>0]
table_mod<-table_mod[order(table_mod,decreasing=TRUE)]
mchemicaldata_origA<-mchemicaldata
#corthresh<-0.5
top_mod<-names(table_mod)
bool_check<-0
final_isp_annot_res_all<-mchemicaldata
level_module_isop_annot<-as.data.frame(level_module_isop_annot)
level_module_isop_annot$Module_RTclust<-gsub(level_module_isop_annot$Module_RTclust,pattern="_[0-9]*",replacement="")
#for(m in 1:length(mchemicaldata$mz))
mchemicaldata_goodadducts_index<-which(mchemicaldata$Adduct%in%as.character(adduct_weights[,1]))
final_isp_annot_res_isp<-{}
if(length(mchemicaldata_goodadducts_index)>0){
final_isp_annot_res_isp<-lapply(1:length(mchemicaldata_goodadducts_index),function(i)
{
m<-mchemicaldata_goodadducts_index[i]
final_isp_annot_res<-cbind(paste("group",i,sep=""),mchemicaldata[m,])
isp_group<-as.character(mchemicaldata$ISgroup[m])
module_rt_group<-as.character(mchemicaldata$Module_RTclust[m])
module_rt_group<-gsub(module_rt_group,pattern="_[0-9]*",replacement="")
isp_mat_module_rt_group<-as.character(level_module_isop_annot$Module_RTclust)
query_md<-mchemicaldata$mz[m]-round(mchemicaldata$mz[m])
query_rt<-mchemicaldata$time[m]
query_int<-1*(mchemicaldata$mean_int_vec[m])
#print(query_int)
#put_isp_masses_curmz_data<-level_module_isop_annot[which(abs((level_module_isop_annot$MD)-(query_md))<0.01 & isp_mat_module_rt_group==module_rt_group & level_module_isop_annot$AvgIntensity<query_int),]
put_isp_masses_curmz_data<-level_module_isop_annot[which(abs(level_module_isop_annot$time-query_rt)<max_diff_rt & abs((level_module_isop_annot$MD)-(query_md))<mass_defect_window & isp_mat_module_rt_group==module_rt_group & level_module_isop_annot$AvgIntensity<query_int),]
#put_isp_masses_curmz_data<-level_module_isop_annot[which(abs((level_module_isop_annot$MD)-(query_md))<mass_defect_window & isp_mat_module_rt_group==module_rt_group & level_module_isop_annot$AvgIntensity<query_int),]
# put_isp_masses_curmz_data<-level_module_isop_annot[which(abs((level_module_isop_annot$MD)-(query_md))<mass_defect_window & isp_mat_module_rt_group==module_rt_group & level_module_isop_annot$AvgIntensity<query_int),]
put_isp_masses_curmz_data<-as.data.frame(put_isp_masses_curmz_data)
put_isp_masses_curmz_data$mz<-as.numeric(as.character(put_isp_masses_curmz_data$mz))
put_isp_masses_curmz_data$time<-as.numeric(as.character(put_isp_masses_curmz_data$time))
mchemicaldata<-as.data.frame(mchemicaldata)
put_isp_masses_curmz_data<-unique(put_isp_masses_curmz_data)
put_isp_masses_curmz_data<-put_isp_masses_curmz_data[order(put_isp_masses_curmz_data$mz),]
if(length(put_isp_masses_curmz_data)>0){
#int_vec<-apply(put_isp_masses_curmz_data[,-c(1:12)],1,max)
int_vec<-put_isp_masses_curmz_data[,c(5)]
int_vec<-int_vec/mchemicaldata[m,13] #(max(int_vec+1,na.rm=TRUE))
curformula<-gsub(curformula,pattern="Sr",replacement="")
curformula<-gsub(curformula,pattern="Sn",replacement="")
curformula<-gsub(curformula,pattern="Se",replacement="")
curformula<-gsub(curformula,pattern="Sc",replacement="")
curformula<-gsub(curformula,pattern="Sm",replacement="")
if(FALSE){
numchlorine<-check_element(curformula,"Cl")
numsulphur<-check_element(curformula,"S")
numbromine<-check_element(curformula,"Br")
max_isp_count<-max(numchlorine,numsulphur,numbromine,max_isp)
}
max_isp_count<-max(exp_isp)
if(is.na(max_isp_count)==TRUE){
max_isp_count=1
}
ischeck<-which(int_vec<=max(abund_ratio_vec[-c(1)]+0.10))
put_isp_masses_curmz_data[,2]<-as.numeric(as.character(put_isp_masses_curmz_data[,2]))
if(length(ischeck)>0){
for(rnum in 1:length(ischeck)){
temp_var<-{}
bool_check<-1
isp_v<-ischeck[rnum]
isp_v<-as.numeric(as.character(isp_v))
#print(isp_v)
#print(put_isp_masses_curmz_data[isp_v,])
# print(mchemicaldata[m,2])
diff_rt<-abs(put_isp_masses_curmz_data[isp_v,2]-mchemicaldata[m,2])
isnum<-(round(put_isp_masses_curmz_data[isp_v,1])-round(mchemicaldata[m,1]))
bool_check<-1
#print(mass_defect_mode)
if(mass_defect_mode=="neg" | mass_defect_mode=="both"){
isnum<-abs(isnum)
}else{
if(isnum>0){
bool_check<-1
}else{
bool_check<-0
}
}
if(diff_rt<max_diff_rt & isnum<=max_isp){
max_isp_count=max_isp
if(max_isp_count>0 && isnum<=max_isp_count && bool_check>0){
isnum2<-(round(put_isp_masses_curmz_data[isp_v,1])-round(mchemicaldata$MonoisotopicMass[m]))
isnum2<-round(isnum2)
if(isnum2<=0){
isp_sign<-"-"
}else{
isp_sign<-"+"
}
#isnum2_orig<-isnum2
isnum2<-abs(isnum2)
if(isnum2<=max_isp)
{
#form_name<-as.character(paste(mchemicaldata[m,7],"_[+",(isnum),"]",sep=""))
form_name<-as.character(paste(mchemicaldata[m,7],"_[",isp_sign,(isnum2),"]",sep=""))
other_inf<-cbind(rep("-",7))
temp_var<-cbind(put_isp_masses_curmz_data[isp_v,c(1:2)],t(other_inf),put_isp_masses_curmz_data[isp_v,c(3:4)],put_isp_masses_curmz_data[isp_v,c(2,5:6)])
temp_var<-as.data.frame(temp_var)
colnames(temp_var)<-colnames(mchemicaldata)
temp_var$Formula<-form_name
temp_var$Name<-as.character(mchemicaldata[m,6])
temp_var$chemical_ID<-as.character(mchemicaldata[m,5])
#temp_var$Adduct<-paste(mchemicaldata[m,9],"_[+",isnum,"]",sep="")
adductname=mchemicaldata[m,9] #queryadductlist[adnum]
#adductmass=adduct_table[as.character(adductname),4]
#temp_var$Adduct<-paste("M","_[",isp_sign,(abs(isnum2)),"]",sep="")
temp_var$Adduct<-paste(mchemicaldata[m,9],"_[",isp_sign,(abs(isnum)),"]",sep="")
temp_var<-as.data.frame(temp_var)
temp_var<-cbind(paste("group",i,sep=""),temp_var)
final_isp_annot_res<-as.data.frame(final_isp_annot_res)
#write.table(temp_var,file="temp_var.txt",sep="\t")
#write.table(final_isp_annot_res,file="final_isp_annot_res.txt",sep="\t")
if(nrow(temp_var)>0){
check_mz<-which(temp_var$mz%in%final_isp_annot_res)
if(length(check_mz)>0){
temp_var<-temp_var[-c(check_mz),]
}
if(nrow(temp_var)>0){
final_isp_annot_res<-rbind(final_isp_annot_res,temp_var)
}
}
}
#write.table(final_isp_annot_res,file="final_isp_annot_res2.txt",sep="\t")
}
}
}
}
}
return(final_isp_annot_res)
})
rm(level_module_isop_annot)
final_isp_annot_res2<-ldply(final_isp_annot_res_isp,rbind)
isp_group_check<-table(final_isp_annot_res2[,1])
good_groups<-which(isp_group_check==max(isp_group_check))
group_name<-names(isp_group_check)[good_groups]
final_isp_annot_res2<-as.data.frame(final_isp_annot_res2)
final_isp_annot_res2<-final_isp_annot_res2 #[which(final_isp_annot_res2[,1]%in%group_name),]
final_isp_annot_res2<-final_isp_annot_res2[,-c(1)]
final_isp_annot_res2<-as.data.frame(final_isp_annot_res2)
rm(final_isp_annot_res_isp)
#write.table(temp_var,file="finaltempvar.txt",sep="\t",row.names=FALSE)
mchemicaldata<-rbind(final_isp_annot_res_all,final_isp_annot_res2) #[,-c(12)]
}
mchemicaldata<-unique(mchemicaldata)
bad_rows<-which(is.na(mchemicaldata$mz)==TRUE)
if(length(bad_rows)>0){
mchemicaldata<-mchemicaldata[-c(bad_rows),]
}
mchemicaldata<-mchemicaldata[order(mchemicaldata$mz),]
mod_names<-mchemicaldata$Module_RTclust
mod_names<-unique(mod_names)
mzid_cur<-paste(mchemicaldata$mz,mchemicaldata$time,sep="_") #mzid_cur<-paste(curmchemdata$mz,curmchemdata$time,sep="_") #mzid_cur<-paste(chem_score$filtdata$mz,chem_score$filtdata$time,sep="_")
temp_global_cor<-global_cor[which(mzid%in%mzid_cur),which(mzid%in%mzid_cur)]
#save(temp_global_cor,file="temp_global_cor.Rda")
#rm(global_cor)
#rm(mzid)
#mzid<-paste(mchemicaldata$mz,mchemicaldata$time,sep="_")
#if(FALSE)
{
diffmatB<-{}
diffmatB<-lapply(1:length(mod_names),function(i){
groupA_num<-mod_names[i]
subdata<-mchemicaldata[which(mchemicaldata$Module_RTclust==groupA_num),]
subdata<-subdata[order(subdata$time),]
if(nrow(subdata)>0){
#print(subdata)
#print(length(subdata))
groupB<-group_by_rt_histv2(subdata,time_step=1,max_diff_rt=10,groupnum=groupA_num)
}else{
groupB<-subdata
}
rownames(groupB)<-NULL
#print(groupB)
return(groupB)
})
mchemicaldata<-ldply(diffmatB,rbind)
}
mchemicaldata<-unique(mchemicaldata)
rm(diffmatB)
dupmz<-{} #which(duplicated(mchemicaldata$mz)==TRUE)
if(length(dupmz)>0){
mchemicaldata<-mchemicaldata[-c(dupmz),]
}
rm(final_isp_annot_res)
write.table(mchemicaldata,file="../Stage2_withisotopes.txt",append=TRUE,sep="\t",col.names=FALSE)
#write.csv(mchemicaldata,file="../Stage2_withisotopes.csv",append=TRUE,col.names=FALSE)
table_mod<-table(mchemicaldata$Module_RTclust)
table_iso<-table(mchemicaldata$ISgroup)
table_mod<-table_mod[table_mod>0]
table_mod<-table_mod[order(table_mod,decreasing=TRUE)]
mchemicaldata_orig<-mchemicaldata
top_mod<-names(table_mod)
bool_check<-0
topquant_cor<-0
best_conf_level<-(-100)
k_power<-1
if(length(which(table_mod>=1))>0)
{
best_chemical_score<-(-100)
for(i in 1:length(which(table_mod>=1)))
{
dup_add<-{}
chemical_score<-(-99999)
conf_level<-0
mchemicaldata<-mchemicaldata_orig[which(mchemicaldata_orig$Module_RTclust==top_mod[i]),]
mchemicaldata<-mchemicaldata[order(mchemicaldata$mz),]
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])",replacement="")
if(nrow(mchemicaldata)<2)
{
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
if(good_adducts_len>0){
chemical_score<-(1*(10^max(as.numeric(as.character(adduct_weights[which(adduct_weights[,1]%in%cur_adducts_with_isotopes),2])))))
chemical_score<-chemical_score[1]
if(chemical_score>best_chemical_score)
{
best_chemical_score<-chemical_score
best_conf_level<-1
best_mod_ind<-i
best_data<-mchemicaldata
}else{
if(chemical_score==best_chemical_score)
{
best_chemical_score<-chemical_score
best_conf_level<-1
best_mod_ind<-c(i,best_mod_ind)
best_data<-rbind(best_data,mchemicaldata)
}
}
}
#next;
}
check2<-gregexpr(text=cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])")
mzid_cur<-paste(mchemicaldata$mz,mchemicaldata$time,sep="_") #mzid_cur<-paste(curmchemdata$mz,curmchemdata$time,sep="_") #mzid_cur<-paste(chem_score$filtdata$mz,chem_score$filtdata$time,sep="_")
dup_features<-which(duplicated(mzid_cur)==TRUE)
if(length(dup_features)>0){
mchemicaldata<-mchemicaldata[-c(dup_features),]
mzid_cur<-paste(mchemicaldata$mz,mchemicaldata$time,sep="_")
}
cor_mz<-global_cor[which(mzid%in%mzid_cur),which(mzid%in%mzid_cur)]
cor_mz<-round(cor_mz,1)
#return(cor_mz)
if(length(cor_mz)>1){
corrownamesA<-rownames(cor_mz)
mat_rownames<-strsplit(as.character(corrownamesA),split="_")
# print(mchemicaldata)
#print(cor_mz)
m1<-{}
for(i in 1:length(mat_rownames)){m1<-rbind(m1,cbind(mat_rownames[[i]] [1],mat_rownames[[i]][2]))}
m1<-as.data.frame(m1)
colnames(m1)<-c("mz","time")
cor_mz2<-cbind(m1,cor_mz)
mz_order<-order(cor_mz2$mz)
cor_mz2<-cor_mz2[c(mz_order),]
cor_mz<-cor_mz2[,-c(1:2)]
cor_mz<-cor_mz[,mz_order]
}
# print(corthresh)
if(length(cor_mz)>1){
check_cor<-sapply(1:dim(cor_mz)[1],function(k){
count_mz<-length(which(cor_mz[k,]>=corthresh))-1
return(count_mz)
})
topquant_cor<-max(cor_mz[upper.tri(cor_mz)])
check_cor2<-check_cor/length(check_cor)
if(length((cur_adducts_with_isotopes%in%adduct_weights[,1]==TRUE))>0){
check_cor[check2>0 | (cur_adducts_with_isotopes%in%adduct_weights[,1]==FALSE)]<-0
}
#return(cor_mz)
#at least score of 2
if(length(which(check_cor>0)==TRUE)>0)
{
#hub_mz<-which(check_cor==max(check_cor)[1] & (cur_adducts_with_isotopes%in%adduct_weights[,1]==TRUE))
hub_mz_list<-which(check_cor>0 & (cur_adducts_with_isotopes%in%filter.by==TRUE))
if(length(hub_mz_list)<1){
hub_mz_list<-which(check_cor>0 & check2<0 & (cur_adducts_with_isotopes%in%adduct_weights[,1]==TRUE))
}
if(length(hub_mz_list)<1){
hub_mz_list<-which(check_cor>0 & check2<0 & (cur_adducts_with_isotopes%in%adduct_weights[,1]==TRUE))
}
if(length(hub_mz_list)<1){
hub_mz_list<-which(check_cor>0 & check2<0)
}
hub_mz_int<-hub_mz_list[which(mchemicaldata$mean_int_vec[hub_mz_list]==max(mchemicaldata$mean_int_vec[hub_mz_list]))[1]]
max_time_neighbors<-0
best_hub_time_mz<-hub_mz_int
for(h1 in hub_mz_list){
mz_name_hub<-paste(mchemicaldata$mz[h1],mchemicaldata$time[h1],sep="_")
hub_rt<-mchemicaldata$time[h1]
diff_rt_hubmz<-apply(mchemicaldata,1,function(k){curtime<-as.numeric(as.character(k[3]));return(abs(hub_rt-curtime))})
num_time_neighbors<-length(which(diff_rt_hubmz<=max_diff_rt))
if(num_time_neighbors>max_time_neighbors){
best_hub_time_mz<-h1
max_time_neighbors<-num_time_neighbors
}
}
#print(best_hub_time_mz)
# print(mchemicaldata)
hub_mz<-best_hub_time_mz
mz_name_hub<-paste(mchemicaldata$mz[hub_mz],mchemicaldata$time[hub_mz],sep="_")
hub_rt<-mchemicaldata$time[hub_mz]
diff_rt_hubmz<-apply(mchemicaldata,1,function(k){curtime<-as.numeric(as.character(k[3]));return(abs(hub_rt-curtime))})
#print(diff_rt_hubmz)
#print(cor_mz)
#print(hub_mz)
#print(mchemicaldata$mean_int_vec)
#print(cor_mz[hub_mz,])
#stop("sf")
if(MplusH.abundance.ratio.check==TRUE){
layer_one_associations<-which(cor_mz[hub_mz,]>=corthresh & mchemicaldata$mean_int_vec<mchemicaldata$mean_int_vec[hub_mz] & diff_rt_hubmz<=max_diff_rt)
}else{
layer_one_associations<-which(cor_mz[hub_mz,]>=corthresh & diff_rt_hubmz<=max_diff_rt)
}
second_level_associations<-{}
for(l in layer_one_associations){
second_level_associations<-c(second_level_associations,which(cor_mz[l,]>=0.7))
}
#print("layer one")
# print(layer_one_associations)
selected_mz<-c(hub_mz,layer_one_associations) #intersect(layer_one_associations,second_level_associations))
selected_mz<-unique(selected_mz)
sub_cor_mz<-cor_mz[hub_mz,which(cor_mz[hub_mz,]>=corthresh)]
#topquant_cor<-quantile(sub_cor_mz,0.9,na.rm=TRUE)[1]
if(is.na(topquant_cor)==TRUE){
topquant_cor=0
}
if(length(which(check_cor2>=0.1))>0){
mchemicaldata<-mchemicaldata[selected_mz,] #[which(cor_mz[hub_mz,]>=corthresh & check_cor2>=0.1),]
#print(mchemicaldata)
}else{
mchemicaldata<-mchemicaldata[which(cor_mz[hub_mz,]>=corthresh),]
}
# print(mchemicaldata)
#return(mchemicaldata)
mchemicaldata<-na.omit(mchemicaldata)
if(nrow(mchemicaldata)<2){
next
}
#print(mchemicaldata)
#print(nrow(mchemicaldata))
mchemicaldata<-as.data.frame(mchemicaldata)
diff_rt<-abs(min(as.numeric(mchemicaldata$time))-max(as.numeric(mchemicaldata$time)))
diff_rt<-round(diff_rt)
if(length(which(is.na(mchemicaldata$time))==TRUE)>0){
mchemicaldata<-mchemicaldata[-which(is.na(mchemicaldata$time)==TRUE),]
}
if(nrow(mchemicaldata)<2){
next
}
if(diff_rt<=max_diff_rt)
{
#print("DOING THIS")
dup_add<-which(duplicated(mchemicaldata$Adduct)==TRUE)
if(length(dup_add)>0){
dup_data<-mchemicaldata[c(dup_add),]
#mchemicaldata<-mchemicaldata[-c(dup_add),]
}
dup_mz_check<-dup_add
#print(dup_add)
#print(mchemicaldata)
if(dim(mchemicaldata)[1]>1){
#chemical_score<-3
k_power<-1
mchemicaldata$time<-as.numeric(as.character(mchemicaldata$time))
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]*\\])",replacement="")
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
#print("score 2")
#chemical_score<-2*2^length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
#change
chemical_score<-length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
#chemical_score<-chemical_score/sqrt(log2((0.5*diff_rt)+1))
#print(chemical_score)
if(good_adducts_len>0){
chemical_score<-sum(chemical_score*(10^max(as.numeric(as.character(adduct_weights[which(adduct_weights[,1]%in%cur_adducts_with_isotopes),2])))))
chemical_score<-chemical_score[1]
}
check2<-gregexpr(text=cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]\\])")
#print(chemical_score)
if(length(which(check2>0))>0){
chemical_score<-100*chemical_score
}
names(chemical_score)<-chemicalid[1]
#print(chemical_score)
if(length(which(mchemicaldata$Adduct%in%adduct_weights[,1]))>0){
fname<-paste(chemicalid,"score.txt",sep="_")
}
}
#return(list("chemical_score"=chemical_score,"filtdata"=mchemicaldata))
}
else{
#print("fixing time")
#return(mchemicaldata)
#mchemicaldata<-chem_score
mchemicaldata$Module_RTclust<-gsub(mchemicaldata$Module_RTclust,pattern="_[0-9]*",replacement="")
mchemicaldata<-cbind(mchemicaldata[,c(2:11)],mchemicaldata[,1],mchemicaldata[,c(12:14)])
colnames(mchemicaldata)<-c("mz","time","MatchCategory","theoretical.mz","chemical_ID","Name","Formula","MonoisotopicMass","Adduct","ISgroup","Module_RTclust","time.y","mean_int_vec", "MD")
#return(mchemicaldata)
mchemicaldata<-as.data.frame(mchemicaldata)
mchemicaldata$time<-as.numeric(as.character(mchemicaldata$time))
#return(mchemicaldata)
groupnumA<-unique(mchemicaldata$Module_RTclust)
mchemicaldata<-group_by_rt_histv2(mchemicaldata,time_step=1,max_diff_rt=max_diff_rt,groupnum=groupnumA)
#print("done")
top_mod_sub<-table(mchemicaldata$Module_RTclust)
top_mod_sub_names<-names(top_mod_sub)
max_top_mod<-which(top_mod_sub==max(top_mod_sub))[1]
mchemicaldata<-mchemicaldata[which(mchemicaldata$Module_RTclust==top_mod_sub_names[max_top_mod]),]
mchemicaldata<-mchemicaldata[order(mchemicaldata$mz),]
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])",replacement="")
#print(mchemicaldata)
d1<-density(mchemicaldata$time,bw=max_diff_rt,from=min(mchemicaldata$time)-0.001,to=(0.01+max(mchemicaldata$time)),na.rm=TRUE)
s1<-summary(d1$x) #mchemicaldata$time)
iqr1<-s1[5]-s1[2]
if(iqr1>max_diff_rt/2){
iqr1<-max_diff_rt/2
}
min_val<-s1[2] #-(1.5*iqr1)
max_val<-s1[5] #+(1.5*iqr1)
{
s1<-summary(mchemicaldata$time)
iqr1<-s1[5]-s1[2]
#print(s1)
min_val<-s1[2]-(1.5*iqr1)
max_val<-s1[5]+(1.5*iqr1)
#print(min_val)
#print(max_val)
if(min_val<s1[1] && max_val>s1[6]){
#min_val<-s1[1]
iqr1<-min(abs(s1[3]-s1[2]),abs(s1[3]-s1[5]))
min_val<-s1[2]-(1.5*iqr1)
max_val<-s1[5]+(1.5*iqr1)
#max_val<-s1[6]
}
#print(mchemicaldata[hub_mz_ind,])
if(min_val<s1[1]){
min_val<-s1[1]
}
if(max_val>s1[6]){
max_val<-s1[6]
}
iqr1<-min(abs(s1[3]-s1[2]),abs(s1[3]-s1[5]))
iqr1<-max(iqr1,max_diff_rt)
diff_rt<-abs(max(mchemicaldata$time)-min(mchemicaldata$time))
# print("fixed time")
# print(diff_rt)
# print(mchemicaldata)
#return(mchemicaldata)
if(nrow(mchemicaldata)<1){
next
}
if(diff_rt>2*max_diff_rt){
time_cor_groups<-sapply(list(myData1=mchemicaldata),function(x) split(x,cut(mchemicaldata$time,breaks=seq(min_val-max_diff_rt,max_val+max_diff_rt,iqr1))))
}else{
max_val<-max(mchemicaldata$time)
min_val<-min(mchemicaldata$time)
diff_rt<-abs(max(mchemicaldata$time)-min(mchemicaldata$time))
if(min_val<max_diff_rt){
#time_cor_groups<-sapply(list(myData1=mchemicaldata),function(x) split(x,cut(mchemicaldata$time,breaks=seq(0,max_val,1*max_diff_rt))))
time_cor_groups<-sapply(list(myData1=mchemicaldata),function(x) split(x,cut(mchemicaldata$time,breaks=c(0,max_val+1))))
}else{
if(diff_rt<max_diff_rt){
time_cor_groups<-sapply(list(myData1=mchemicaldata),function(x) split(x,cut(mchemicaldata$time,breaks=c(min_val-diff_rt,max_val+diff_rt,diff_rt*2))))
}else{
time_cor_groups<-sapply(list(myData1=mchemicaldata),function(x) split(x,cut(mchemicaldata$time,breaks=seq(min_val-diff_rt,max_val+diff_rt,1*max_diff_rt))))
}
}
}
}
#return(time_cor_groups)
group_sizes<-sapply(time_cor_groups,function(x){dim(as.data.frame(x))[1]})
group_ind_val<-1
group_ind_size<-1
check_reladd<-{}
check_data<-{}
if(length(which(group_sizes>1))>0){
group_ind_val<-which(group_sizes==max(group_sizes)[1])
}
group_ind_size<-max(group_sizes)[1]
if(group_ind_size<2){
k_power<-1.25
mchemicaldata<-mchemicaldata_orig[which(mchemicaldata_orig$Module_RTclust==top_mod[i]),]
mchemicaldata<-mchemicaldata[order(mchemicaldata$mz),]
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])",replacement="")
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
# chemical_score<-length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))*(1/((diff_rt*0.1)+1)^k_power)
#change
chemical_score<-length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
if(good_adducts_len>0){
chemical_score<-sum(chemical_score*(as.numeric(adduct_weights[which(adduct_weights[,1]%in%cur_adducts),2])))
}
}
good_temp<-{}
for(g1 in 1:length(group_sizes))
{
tempdata<-time_cor_groups[[g1]]
check_reladd<-which(tempdata$Adduct%in%as.character(adduct_weights[,1]))
if(length(check_reladd)>0){
good_temp<-c(good_temp,g1)
if(nrow(tempdata)>group_ind_size){
group_ind_val<-g1
group_ind_size<-nrow(tempdata)
}
}
}
if(length(which(group_sizes>1))>0)
{
temp_best_score<-(-100)
temp_best_data<-{}
for(g2 in 1:length(group_sizes)){
if(g2%in%good_temp){
mchemicaldata<-{}
mchemicaldata<-rbind(mchemicaldata,time_cor_groups[[g2]])
mchemicaldata<-as.data.frame(mchemicaldata)
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])",replacement="")
if(length(mchemicaldata)<1){
next
}
if(nrow(mchemicaldata)<1){
next
}
diff_rt<-abs(min(as.numeric(mchemicaldata$time))-max(as.numeric(mchemicaldata$time)))
diff_rt<-round(diff_rt)
#print("diff rT")
#print(diff_rt)
#print(mchemicaldata)
dup_add<-{} #which(duplicated(mchemicaldata$Adduct)==TRUE)
if(length(dup_add)>0){
dup_data<-mchemicaldata[c(dup_add),]
#mchemicaldata<-mchemicaldata[-c(dup_add),]
}
if(length(mchemicaldata)<1){
next
}
if(nrow(mchemicaldata)<1){
next
}
if(diff_rt<=max_diff_rt)
{
if(dim(mchemicaldata)[1]>1)
{
k_power<-1
mchemicaldata$time<-as.numeric(as.character(mchemicaldata$time))
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]*\\])",replacement="")
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
#print("score 3")
#chemical_score<-2*2^length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
#change
chemical_score<-length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
#chemical_score<-chemical_score/sqrt(log2((0.5*diff_rt)+1))
if(good_adducts_len>0){
#chemical_score<-chemical_score*(2^adduct_weights[which(adduct_weights[,1]%in%cur_adducts),2])
chemical_score<-sum(chemical_score*(10^max(as.numeric(as.character(adduct_weights[which(adduct_weights[,1]%in%cur_adducts_with_isotopes),2])))))
chemical_score<-chemical_score[1]
}
check2<-gregexpr(text=cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]*\\])")
if(length(which(check2>0))>0){
chemical_score<-100*chemical_score
}
}else{
chemical_score<-0
}
names(chemical_score)<-chemicalid[1]
}else{
d1<-density(mchemicaldata$time,bw=max_diff_rt,from=min(mchemicaldata$time)-0.001,to=(0.01+max(mchemicaldata$time)),na.rm=TRUE)
s1<-summary(d1$x)
iqr1<-s1[5]-s1[2]
if(iqr1>max_diff_rt/2){
iqr1<-max_diff_rt/2
}
min_val<-s1[2] #-(1.5*iqr1)
max_val<-s1[5] #+(1.5*iqr1)
if(length(which(mchemicaldata$time>=min_val & mchemicaldata$time<=max_val))>1)
{
mchemicaldata<-mchemicaldata[which(mchemicaldata$time>=(min_val-1) & mchemicaldata$time<=(max_val-1)),]
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])",replacement="")
if(dim(mchemicaldata)[1]>1)
{
k_power<-1
mchemicaldata$time<-as.numeric(as.character(mchemicaldata$time))
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]*\\])",replacement="")
# print("Setting score 3")
#print(mchemicaldata)
# chemical_score<-100*2^length(which(cur_adducts%in%adduct_weights[,1]))+1*(topquant_cor)*(1/((diff_rt*0.1)+1)^k_power) #*length(unique(cur_adducts))
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
#print("score 4")
#chemical_score<-2*2^length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
#change
chemical_score<-length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
#chemical_score<-chemical_score/sqrt(log2((0.5*diff_rt)+1))
if(good_adducts_len>0){
#chemical_score<-chemical_score*(2^adduct_weights[which(adduct_weights[,1]%in%cur_adducts),2])
chemical_score<-sum(chemical_score*(10^max(as.numeric(as.character(adduct_weights[which(adduct_weights[,1]%in%cur_adducts_with_isotopes),2])))))
chemical_score<-chemical_score[1]
}
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]*\\])",replacement="")
check2<-gregexpr(text=cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]\\])")
if(length(which(check2>0))>0){
chemical_score<-100*chemical_score
}
#*(1/((diff_rt*0.1)+1)^k_power))
}
names(chemical_score)<-chemicalid[1]
}else{
# print("Setting score 4")
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]*\\])",replacement="")
#print("score 5")
#chemical_score<-0
# chemical_score<-length(which(cur_adducts%in%adduct_weights[,1]))+1*(topquant_cor)*(1/((diff_rt*0.1)+1)^k_power)
chemical_score<-length(unique(cur_adducts))*length(which(cur_adducts%in%adduct_weights[,1]))*(1*(topquant_cor)*(1/((diff_rt*0.1)+1)^k_power))
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
#change
chemical_score<-length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
if(good_adducts_len>0){
chemical_score<-sum(chemical_score*(as.numeric(adduct_weights[which(adduct_weights[,1]%in%cur_adducts),2])))
}
names(chemical_score)<-chemicalid[1]
}
}
if(chemical_score>temp_best_score)
{
temp_best_data<-mchemicaldata
mchemicaldata<-temp_best_data
temp_best_score<-chemical_score
}
}
}
mchemicaldata<-temp_best_data
chemical_score<-temp_best_score
}
else{
#v1.4.1 removed duplicate
#dup_mz_check<-which(duplicated(mchemicaldata$Adduct)==TRUE)
# if(length(dup_mz_check)>0){
# mchemicaldata<-mchemicaldata[-c(dup_mz_check),]
#chemical_score<-0
#chemical_score<-length(which(cur_adducts%in%adduct_weights[,1]))+1*(topquant_cor)*(1/((diff_rt*0.1)+1)^k_power)
#names(chemical_score)<-chemicalid[1]
# }
if(dim(mchemicaldata)[1]>1){
diff_rt<-abs(min(as.numeric(mchemicaldata$time))-max(as.numeric(mchemicaldata$time)))
d1<-density(mchemicaldata$time,bw=max_diff_rt,from=min(mchemicaldata$time)-0.001,to=(0.01+max(mchemicaldata$time)),na.rm=TRUE)
s1<-summary(d1$x) #mchemicaldata$time)
iqr1<-s1[5]-s1[2]
if(iqr1>max_diff_rt/2){
iqr1<-max_diff_rt/2
}
min_val<-s1[2] #-(1.5*iqr1)
max_val<-s1[5] #+(1.5*iqr1)
if(length(which(mchemicaldata$time>=min_val & mchemicaldata$time<=max_val))>1)
{
mchemicaldata<-mchemicaldata[which(mchemicaldata$time>=min_val & mchemicaldata$time<=max_val),]
dup_add<-which(duplicated(mchemicaldata$Adduct)==TRUE)
if(length(dup_add)>0){
dup_data<-mchemicaldata[c(dup_add),]
#mchemicaldata<-mchemicaldata[-c(dup_add),]
}
if(dim(mchemicaldata)[1]>1)
{
k_power<-1
mchemicaldata$time<-as.numeric(as.character(mchemicaldata$time))
dup_add<-which(duplicated(mchemicaldata$Adduct)==TRUE)
if(length(dup_add)>0){
dup_data<-mchemicaldata[c(dup_add),]
#mchemicaldata<-mchemicaldata[-c(dup_add),]
}
if(length(mchemicaldata)>0){
if(nrow(mchemicaldata)>1){
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])",replacement="")
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
#print("score 6")
# chemical_score<-2*2^length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
#change
chemical_score<-length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
#chemical_score<-chemical_score/sqrt(log2((0.5*diff_rt)+1))
if(good_adducts_len>0){
chemical_score<-sum(chemical_score*(10^max(as.numeric(as.character(adduct_weights[which(adduct_weights[,1]%in%cur_adducts_with_isotopes),2])))))
chemical_score<-chemical_score[1]
}
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]*\\])",replacement="")
check2<-gregexpr(text=cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]*\\])")
if(length(which(check2>0))>0){
chemical_score<-100*chemical_score
}
}else{
chemical_score<-0
}
}else{
chemical_score<-0
}
}
names(chemical_score)<-chemicalid[1]
}else
{
dup_add<-which(duplicated(mchemicaldata$Adduct)==TRUE)
if(length(dup_add)>0){
dup_data<-mchemicaldata[c(dup_add),]
#mchemicaldata<-mchemicaldata[-c(dup_add),]
}
if(length(mchemicaldata)>0){
if(nrow(mchemicaldata)>1){
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])",replacement="")
if(diff_rt>max_diff_rt){
k_power<-3
# print("score 7")
#chemical_score<-0
#length(unique(cur_adducts))*length(which(cur_adducts%in%adduct_weights[,1]))*(1*(topquant_cor)*(1/((diff_rt*0.1)+1)^k_power))
chemical_score<-length(unique(cur_adducts))*length(which(cur_adducts%in%adduct_weights[,1]))*(1*(topquant_cor)*(1/((diff_rt*0.1)+1)^k_power))
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
#change
chemical_score<-length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
if(good_adducts_len>0){
chemical_score<-sum(chemical_score*(as.numeric(adduct_weights[which(adduct_weights[,1]%in%cur_adducts),2])))
}
}
}else{
chemical_score<-0
#chemical_score<-length(which(cur_adducts%in%adduct_weights[,1]))+1*(topquant_cor)*(1/((diff_rt*0.1)+1)^k_power)
}
}else{
chemical_score<-0
}
}
#chemical_score<-(topquant_cor)*(1/(diff_rt+1)^k_power)*length(unique(mchemicaldata$Adduct))
#print("setting score 6")
}
names(chemical_score)<-chemicalid[1]
}
names(chemical_score)<-chemicalid[1]
mchemicaldata<-mchemicaldata #[,c(1:11)]
mchemicaldata<-na.omit(mchemicaldata)
if(length(which(mchemicaldata$Adduct%in%adduct_weights[,1]))>0){
# return(list("chemical_score"=chemical_score,"filtdata"=mchemicaldata))
}
}
}
else{
#no correlation between putative adducts
#print("setting score 7")
cur_adducts_with_isotopes<-mchemicaldata$Adduct
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
#print(mchemicaldata)
if(good_adducts_len>0)
{
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]*\\])",replacement="")
max_adduct_weight<-max(as.numeric(as.character(adduct_weights[which(adduct_weights[,1]%in%cur_adducts_with_isotopes),2])))[1]
chemical_score<-((10^max_adduct_weight))
#print("score 7")
chemical_score<-chemical_score[1]
good_adduct_index<-which(adduct_weights[,2]==max_adduct_weight)
chemical_score<-chemical_score[1]
mchemicaldata<-mchemicaldata[which(cur_adducts_with_isotopes%in%adduct_weights[good_adduct_index,1]),]
if(FALSE){
if(chemical_score>best_chemical_score)
{
best_chemical_score<-chemical_score
best_conf_level<-1
best_mod_ind<-i
best_data<-mchemicaldata
}
}
}else{
#
chemical_score<-0
mchemicaldata<-mchemicaldata_orig[which(mchemicaldata_orig$Module_RTclust==top_mod[i]),]
mchemicaldata<-mchemicaldata[order(mchemicaldata$mz),]
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])",replacement="")
#next;
}
}
}
#mchemicaldata<-mchemicaldata[order(mchemicaldata$Adduct),]
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])",replacement="")
check2<-gregexpr(text=cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])")
if(length(check2)>0){
for(a1 in 1:length(check2)){
strlength<-attr(check2[[a1]],"match.length")
if(strlength[1]>(-1)){
count_abundant_form<-length(which(cur_adducts%in%cur_adducts[a1]))
if(count_abundant_form<2)
{
chemscoremat_conf_levels<-"None"
mchemicaldata<-mchemicaldata[-a1,]
}
}
}
}
#if(nrow(mchemicaldata)<1){
conf_level<-0
if(length(mchemicaldata)<1){
conf_level<-0
}else{
if(nrow(mchemicaldata)>0){
conf_level<-get_confidence_stage2(curdata=mchemicaldata,adduct_weights=adduct_weights)
conf_level<-as.numeric(as.character(conf_level))
}else{
conf_level<-0
}
}
if(length(mchemicaldata)>0){
if(nrow(mchemicaldata)>1){
diff_rt<-max(mchemicaldata$time)-min(mchemicaldata$time)
k_power=1
if(diff_rt>max_diff_rt)
{
k_power=10
}
chemical_score<-chemical_score*(1/((diff_rt*0.1)+1)^k_power)
}
}else{
chemical_score<-0
}
min_chemical_score<-100*2*(1*(corthresh))*(1/((max_diff_rt*0.1)+1)^3)
if(chemical_score>min_chemical_score){
chemical_score<-chemical_score*(conf_level^conf_level)
}else{
chemical_score<-0
}
if(length(dup_add)>0){
mchemicaldata<-rbind(mchemicaldata,dup_data)
}
if(is.na(conf_level)==TRUE){
conf_level<-0
}
if(is.na(chemical_score)==TRUE){
chemical_score<-0
}
if(chemical_score>best_chemical_score & conf_level>0) #| conf_level>=best_conf_level)
{
best_chemical_score<-chemical_score
best_conf_level<-conf_level
best_mod_ind<-i
best_data<-mchemicaldata
}else{
if(chemical_score==best_chemical_score)
{
best_chemical_score<-chemical_score
best_conf_level<-1
best_mod_ind<-c(i,best_mod_ind)
best_data<-rbind(best_data,mchemicaldata)
}
}
if(FALSE)
{
print("i is")
print(i)
print(mchemicaldata)
print(top_mod[i])
print("score is")
print(chemical_score)
print(best_chemical_score)
print("conf level")
print(conf_level)
}
}
##for loop complete
if(best_chemical_score>0){
chemical_score<-best_chemical_score
best_mod<-best_mod_ind
mchemicaldata<-best_data
names(chemical_score)<-chemicalid[1]
#return(list("chemical_score"=chemical_score,"filtdata"=mchemicaldata))
}else{
chemical_score<-0
}
}
#######add code for only correlation criteria here
#if(FALSE)
{
#if(chemical_score<=0)
#print("length is")
#print(length(which(mchemicaldata$Adduct%in%as.character(filter.by))))
if(chemical_score<=1) # || length(which(mchemicaldata$Adduct%in%as.character(filter.by)))<1)
{
mchemicaldata<-mchemicaldata_orig
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]*\\])",replacement="")
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
if(good_adducts_len>0)
{
max_adduct_weight<-max(as.numeric(as.character(adduct_weights[which(adduct_weights[,1]%in%cur_adducts_with_isotopes),2])))[1]
chemical_score<-((10^max_adduct_weight))
chemical_score<-chemical_score[1]-1
good_adduct_index<-which(adduct_weights[,2]==max_adduct_weight)
chemical_score<-chemical_score[1]
mchemicaldata<-mchemicaldata[which(cur_adducts_with_isotopes%in%adduct_weights[good_adduct_index,1]),]
}
}
}
if(nrow(mchemicaldata)>0){
mchemicaldata<-unique(mchemicaldata)
mzid_cur<-paste(mchemicaldata$mz,mchemicaldata$time,sep="_")
#dweight1<-degree_weights[which(mzid%in%mzid_cur),]
}else{
dweight1<-c(0)
chemical_score<-0
}
#
#print(best_chemical_score)
rm("mzid","global_cor","temp_global_cor")
return(list("chemical_score"=chemical_score,"filtdata"=mchemicaldata))
}
}
yufree/xMSannotator documentation built on Oct. 31, 2022, 12:20 a.m.
R Package Documentation
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Defines functions get_chemscorev1.6.71
get_chemscorev1.6.71 <-
function(chemicalid,mchemicaldata,corthresh,global_cor,mzid,max_diff_rt=10,level_module_isop_annot,
adduct_table,adduct_weights,filter.by=c("M+H"),max_isp=100, MplusH.abundance.ratio.check=TRUE,mass_defect_window=0.01,mass_defect_mode="pos",outlocorig)
{
#new
#print("here")
setwd(outlocorig)
# load("step1_results.Rda")
# load("global_cor.Rda")
outloc1<-paste(outlocorig,"/stage2/",sep="")
suppressWarnings(dir.create(outloc1))
setwd(outloc1)
mchemicaldata$mz<-as.numeric(as.character(mchemicaldata$mz))
mchemicaldata$time<-as.numeric(as.character(mchemicaldata$time))
mchemicaldata$MonoisotopicMass<-as.numeric(as.character(mchemicaldata$MonoisotopicMass))
level_module_isop_annot$mz<-as.numeric(as.character(level_module_isop_annot$mz))
level_module_isop_annot$time<-as.numeric(as.character(level_module_isop_annot$time))
chemical_score<-(-100)
fname<-paste(chemicalid,"data.txt",sep="_")
if(length(mchemicaldata$mz)>0){
if(length(which(duplicated(mchemicaldata$mz)==TRUE))>0){
# mchemicaldata<-mchemicaldata[-which(duplicated(mchemicaldata$mz)==TRUE),]
}
mchemicaldata$Module_RTclust<-gsub(mchemicaldata$Module_RTclust,pattern="_[0-9]*",replacement="")
mchemicaldata_orig<-mchemicaldata
#if(FALSE)
{
if(length(which(mchemicaldata_orig$Adduct%in%as.character(adduct_weights[,1])))>0){
rel_adduct_data<-mchemicaldata[which(mchemicaldata$Adduct%in%as.character(adduct_weights[,1])),]
rel_adduct_module<-gsub(rel_adduct_data$Module_RTclust,pattern="_[0-9]*",replacement="")
module_rt_group<-gsub(mchemicaldata$Module_RTclust,pattern="_[0-9]*",replacement="")
mchemicaldata<-mchemicaldata[which(module_rt_group%in%rel_adduct_module),]
}
}
mchemicaldata<-unique(mchemicaldata)
curformula<-as.character(mchemicaldata[,7])
formula_check<-getMolecule(as.character(curformula[1]))
exp_isp<-which(formula_check$isotopes[[1]][2,]>=0.001)
#print(formula_check)
#print(exp_isp)
abund_ratio_vec<-formula_check$isotopes[[1]][2,exp_isp]
numoxygen<-check_element(curformula,"O")
water_adducts<-c("M+H-H2O","M+H-2H2O","M-H2O-H")
water_adduct_ind<-which(mchemicaldata$Adduct%in%water_adducts)
if(numoxygen<1){
if(length(water_adduct_ind)>0){
mchemicaldata<-mchemicaldata[-water_adduct_ind,]
}
}
#water check
if(nrow(mchemicaldata)<1){
chemical_score<-(-100)
return(list("chemical_score"=chemical_score,"filtdata"=mchemicaldata))
}
mchemicaldata$Adduct<-as.character(mchemicaldata$Adduct)
uniq_adducts<-unique(mchemicaldata$Adduct)
good_adducts<-uniq_adducts[which(uniq_adducts%in%as.character(adduct_weights[,1]))]
table_mod<-table(mchemicaldata$Module_RTclust)
table_iso<-table(mchemicaldata$ISgroup)
table_mod<-table_mod[table_mod>0]
table_mod<-table_mod[order(table_mod,decreasing=TRUE)]
mchemicaldata_origA<-mchemicaldata
#corthresh<-0.5
top_mod<-names(table_mod)
bool_check<-0
final_isp_annot_res_all<-mchemicaldata
level_module_isop_annot<-as.data.frame(level_module_isop_annot)
level_module_isop_annot$Module_RTclust<-gsub(level_module_isop_annot$Module_RTclust,pattern="_[0-9]*",replacement="")
#for(m in 1:length(mchemicaldata$mz))
mchemicaldata_goodadducts_index<-which(mchemicaldata$Adduct%in%as.character(adduct_weights[,1]))
final_isp_annot_res_isp<-{}
if(length(mchemicaldata_goodadducts_index)>0){
final_isp_annot_res_isp<-lapply(1:length(mchemicaldata_goodadducts_index),function(i)
{
m<-mchemicaldata_goodadducts_index[i]
final_isp_annot_res<-cbind(paste("group",i,sep=""),mchemicaldata[m,])
isp_group<-as.character(mchemicaldata$ISgroup[m])
module_rt_group<-as.character(mchemicaldata$Module_RTclust[m])
module_rt_group<-gsub(module_rt_group,pattern="_[0-9]*",replacement="")
isp_mat_module_rt_group<-as.character(level_module_isop_annot$Module_RTclust)
query_md<-mchemicaldata$mz[m]-round(mchemicaldata$mz[m])
query_rt<-mchemicaldata$time[m]
query_int<-1*(mchemicaldata$mean_int_vec[m])
#print(query_int)
#put_isp_masses_curmz_data<-level_module_isop_annot[which(abs((level_module_isop_annot$MD)-(query_md))<0.01 & isp_mat_module_rt_group==module_rt_group & level_module_isop_annot$AvgIntensity<query_int),]
put_isp_masses_curmz_data<-level_module_isop_annot[which(abs(level_module_isop_annot$time-query_rt)<max_diff_rt & abs((level_module_isop_annot$MD)-(query_md))<mass_defect_window & isp_mat_module_rt_group==module_rt_group & level_module_isop_annot$AvgIntensity<query_int),]
#put_isp_masses_curmz_data<-level_module_isop_annot[which(abs((level_module_isop_annot$MD)-(query_md))<mass_defect_window & isp_mat_module_rt_group==module_rt_group & level_module_isop_annot$AvgIntensity<query_int),]
# put_isp_masses_curmz_data<-level_module_isop_annot[which(abs((level_module_isop_annot$MD)-(query_md))<mass_defect_window & isp_mat_module_rt_group==module_rt_group & level_module_isop_annot$AvgIntensity<query_int),]
put_isp_masses_curmz_data<-as.data.frame(put_isp_masses_curmz_data)
put_isp_masses_curmz_data$mz<-as.numeric(as.character(put_isp_masses_curmz_data$mz))
put_isp_masses_curmz_data$time<-as.numeric(as.character(put_isp_masses_curmz_data$time))
mchemicaldata<-as.data.frame(mchemicaldata)
put_isp_masses_curmz_data<-unique(put_isp_masses_curmz_data)
put_isp_masses_curmz_data<-put_isp_masses_curmz_data[order(put_isp_masses_curmz_data$mz),]
if(length(put_isp_masses_curmz_data)>0){
#int_vec<-apply(put_isp_masses_curmz_data[,-c(1:12)],1,max)
int_vec<-put_isp_masses_curmz_data[,c(5)]
int_vec<-int_vec/mchemicaldata[m,13] #(max(int_vec+1,na.rm=TRUE))
curformula<-gsub(curformula,pattern="Sr",replacement="")
curformula<-gsub(curformula,pattern="Sn",replacement="")
curformula<-gsub(curformula,pattern="Se",replacement="")
curformula<-gsub(curformula,pattern="Sc",replacement="")
curformula<-gsub(curformula,pattern="Sm",replacement="")
if(FALSE){
numchlorine<-check_element(curformula,"Cl")
numsulphur<-check_element(curformula,"S")
numbromine<-check_element(curformula,"Br")
max_isp_count<-max(numchlorine,numsulphur,numbromine,max_isp)
}
max_isp_count<-max(exp_isp)
if(is.na(max_isp_count)==TRUE){
max_isp_count=1
}
ischeck<-which(int_vec<=max(abund_ratio_vec[-c(1)]+0.10))
put_isp_masses_curmz_data[,2]<-as.numeric(as.character(put_isp_masses_curmz_data[,2]))
if(length(ischeck)>0){
for(rnum in 1:length(ischeck)){
temp_var<-{}
bool_check<-1
isp_v<-ischeck[rnum]
isp_v<-as.numeric(as.character(isp_v))
#print(isp_v)
#print(put_isp_masses_curmz_data[isp_v,])
# print(mchemicaldata[m,2])
diff_rt<-abs(put_isp_masses_curmz_data[isp_v,2]-mchemicaldata[m,2])
isnum<-(round(put_isp_masses_curmz_data[isp_v,1])-round(mchemicaldata[m,1]))
bool_check<-1
#print(mass_defect_mode)
if(mass_defect_mode=="neg" | mass_defect_mode=="both"){
isnum<-abs(isnum)
}else{
if(isnum>0){
bool_check<-1
}else{
bool_check<-0
}
}
if(diff_rt<max_diff_rt & isnum<=max_isp){
max_isp_count=max_isp
if(max_isp_count>0 && isnum<=max_isp_count && bool_check>0){
isnum2<-(round(put_isp_masses_curmz_data[isp_v,1])-round(mchemicaldata$MonoisotopicMass[m]))
isnum2<-round(isnum2)
if(isnum2<=0){
isp_sign<-"-"
}else{
isp_sign<-"+"
}
#isnum2_orig<-isnum2
isnum2<-abs(isnum2)
if(isnum2<=max_isp)
{
#form_name<-as.character(paste(mchemicaldata[m,7],"_[+",(isnum),"]",sep=""))
form_name<-as.character(paste(mchemicaldata[m,7],"_[",isp_sign,(isnum2),"]",sep=""))
other_inf<-cbind(rep("-",7))
temp_var<-cbind(put_isp_masses_curmz_data[isp_v,c(1:2)],t(other_inf),put_isp_masses_curmz_data[isp_v,c(3:4)],put_isp_masses_curmz_data[isp_v,c(2,5:6)])
temp_var<-as.data.frame(temp_var)
colnames(temp_var)<-colnames(mchemicaldata)
temp_var$Formula<-form_name
temp_var$Name<-as.character(mchemicaldata[m,6])
temp_var$chemical_ID<-as.character(mchemicaldata[m,5])
#temp_var$Adduct<-paste(mchemicaldata[m,9],"_[+",isnum,"]",sep="")
adductname=mchemicaldata[m,9] #queryadductlist[adnum]
#adductmass=adduct_table[as.character(adductname),4]
#temp_var$Adduct<-paste("M","_[",isp_sign,(abs(isnum2)),"]",sep="")
temp_var$Adduct<-paste(mchemicaldata[m,9],"_[",isp_sign,(abs(isnum)),"]",sep="")
temp_var<-as.data.frame(temp_var)
temp_var<-cbind(paste("group",i,sep=""),temp_var)
final_isp_annot_res<-as.data.frame(final_isp_annot_res)
#write.table(temp_var,file="temp_var.txt",sep="\t")
#write.table(final_isp_annot_res,file="final_isp_annot_res.txt",sep="\t")
if(nrow(temp_var)>0){
check_mz<-which(temp_var$mz%in%final_isp_annot_res)
if(length(check_mz)>0){
temp_var<-temp_var[-c(check_mz),]
}
if(nrow(temp_var)>0){
final_isp_annot_res<-rbind(final_isp_annot_res,temp_var)
}
}
}
#write.table(final_isp_annot_res,file="final_isp_annot_res2.txt",sep="\t")
}
}
}
}
}
return(final_isp_annot_res)
})
rm(level_module_isop_annot)
final_isp_annot_res2<-ldply(final_isp_annot_res_isp,rbind)
isp_group_check<-table(final_isp_annot_res2[,1])
good_groups<-which(isp_group_check==max(isp_group_check))
group_name<-names(isp_group_check)[good_groups]
final_isp_annot_res2<-as.data.frame(final_isp_annot_res2)
final_isp_annot_res2<-final_isp_annot_res2 #[which(final_isp_annot_res2[,1]%in%group_name),]
final_isp_annot_res2<-final_isp_annot_res2[,-c(1)]
final_isp_annot_res2<-as.data.frame(final_isp_annot_res2)
rm(final_isp_annot_res_isp)
#write.table(temp_var,file="finaltempvar.txt",sep="\t",row.names=FALSE)
mchemicaldata<-rbind(final_isp_annot_res_all,final_isp_annot_res2) #[,-c(12)]
}
mchemicaldata<-unique(mchemicaldata)
bad_rows<-which(is.na(mchemicaldata$mz)==TRUE)
if(length(bad_rows)>0){
mchemicaldata<-mchemicaldata[-c(bad_rows),]
}
mchemicaldata<-mchemicaldata[order(mchemicaldata$mz),]
mod_names<-mchemicaldata$Module_RTclust
mod_names<-unique(mod_names)
mzid_cur<-paste(mchemicaldata$mz,mchemicaldata$time,sep="_") #mzid_cur<-paste(curmchemdata$mz,curmchemdata$time,sep="_") #mzid_cur<-paste(chem_score$filtdata$mz,chem_score$filtdata$time,sep="_")
temp_global_cor<-global_cor[which(mzid%in%mzid_cur),which(mzid%in%mzid_cur)]
#save(temp_global_cor,file="temp_global_cor.Rda")
#rm(global_cor)
#rm(mzid)
#mzid<-paste(mchemicaldata$mz,mchemicaldata$time,sep="_")
#if(FALSE)
{
diffmatB<-{}
diffmatB<-lapply(1:length(mod_names),function(i){
groupA_num<-mod_names[i]
subdata<-mchemicaldata[which(mchemicaldata$Module_RTclust==groupA_num),]
subdata<-subdata[order(subdata$time),]
if(nrow(subdata)>0){
#print(subdata)
#print(length(subdata))
groupB<-group_by_rt_histv2(subdata,time_step=1,max_diff_rt=10,groupnum=groupA_num)
}else{
groupB<-subdata
}
rownames(groupB)<-NULL
#print(groupB)
return(groupB)
})
mchemicaldata<-ldply(diffmatB,rbind)
}
mchemicaldata<-unique(mchemicaldata)
rm(diffmatB)
dupmz<-{} #which(duplicated(mchemicaldata$mz)==TRUE)
if(length(dupmz)>0){
mchemicaldata<-mchemicaldata[-c(dupmz),]
}
rm(final_isp_annot_res)
write.table(mchemicaldata,file="../Stage2_withisotopes.txt",append=TRUE,sep="\t",col.names=FALSE)
#write.csv(mchemicaldata,file="../Stage2_withisotopes.csv",append=TRUE,col.names=FALSE)
table_mod<-table(mchemicaldata$Module_RTclust)
table_iso<-table(mchemicaldata$ISgroup)
table_mod<-table_mod[table_mod>0]
table_mod<-table_mod[order(table_mod,decreasing=TRUE)]
mchemicaldata_orig<-mchemicaldata
top_mod<-names(table_mod)
bool_check<-0
topquant_cor<-0
best_conf_level<-(-100)
k_power<-1
if(length(which(table_mod>=1))>0)
{
best_chemical_score<-(-100)
for(i in 1:length(which(table_mod>=1)))
{
dup_add<-{}
chemical_score<-(-99999)
conf_level<-0
mchemicaldata<-mchemicaldata_orig[which(mchemicaldata_orig$Module_RTclust==top_mod[i]),]
mchemicaldata<-mchemicaldata[order(mchemicaldata$mz),]
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])",replacement="")
if(nrow(mchemicaldata)<2)
{
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
if(good_adducts_len>0){
chemical_score<-(1*(10^max(as.numeric(as.character(adduct_weights[which(adduct_weights[,1]%in%cur_adducts_with_isotopes),2])))))
chemical_score<-chemical_score[1]
if(chemical_score>best_chemical_score)
{
best_chemical_score<-chemical_score
best_conf_level<-1
best_mod_ind<-i
best_data<-mchemicaldata
}else{
if(chemical_score==best_chemical_score)
{
best_chemical_score<-chemical_score
best_conf_level<-1
best_mod_ind<-c(i,best_mod_ind)
best_data<-rbind(best_data,mchemicaldata)
}
}
}
#next;
}
check2<-gregexpr(text=cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])")
mzid_cur<-paste(mchemicaldata$mz,mchemicaldata$time,sep="_") #mzid_cur<-paste(curmchemdata$mz,curmchemdata$time,sep="_") #mzid_cur<-paste(chem_score$filtdata$mz,chem_score$filtdata$time,sep="_")
dup_features<-which(duplicated(mzid_cur)==TRUE)
if(length(dup_features)>0){
mchemicaldata<-mchemicaldata[-c(dup_features),]
mzid_cur<-paste(mchemicaldata$mz,mchemicaldata$time,sep="_")
}
cor_mz<-global_cor[which(mzid%in%mzid_cur),which(mzid%in%mzid_cur)]
cor_mz<-round(cor_mz,1)
#return(cor_mz)
if(length(cor_mz)>1){
corrownamesA<-rownames(cor_mz)
mat_rownames<-strsplit(as.character(corrownamesA),split="_")
# print(mchemicaldata)
#print(cor_mz)
m1<-{}
for(i in 1:length(mat_rownames)){m1<-rbind(m1,cbind(mat_rownames[[i]] [1],mat_rownames[[i]][2]))}
m1<-as.data.frame(m1)
colnames(m1)<-c("mz","time")
cor_mz2<-cbind(m1,cor_mz)
mz_order<-order(cor_mz2$mz)
cor_mz2<-cor_mz2[c(mz_order),]
cor_mz<-cor_mz2[,-c(1:2)]
cor_mz<-cor_mz[,mz_order]
}
# print(corthresh)
if(length(cor_mz)>1){
check_cor<-sapply(1:dim(cor_mz)[1],function(k){
count_mz<-length(which(cor_mz[k,]>=corthresh))-1
return(count_mz)
})
topquant_cor<-max(cor_mz[upper.tri(cor_mz)])
check_cor2<-check_cor/length(check_cor)
if(length((cur_adducts_with_isotopes%in%adduct_weights[,1]==TRUE))>0){
check_cor[check2>0 | (cur_adducts_with_isotopes%in%adduct_weights[,1]==FALSE)]<-0
}
#return(cor_mz)
#at least score of 2
if(length(which(check_cor>0)==TRUE)>0)
{
#hub_mz<-which(check_cor==max(check_cor)[1] & (cur_adducts_with_isotopes%in%adduct_weights[,1]==TRUE))
hub_mz_list<-which(check_cor>0 & (cur_adducts_with_isotopes%in%filter.by==TRUE))
if(length(hub_mz_list)<1){
hub_mz_list<-which(check_cor>0 & check2<0 & (cur_adducts_with_isotopes%in%adduct_weights[,1]==TRUE))
}
if(length(hub_mz_list)<1){
hub_mz_list<-which(check_cor>0 & check2<0 & (cur_adducts_with_isotopes%in%adduct_weights[,1]==TRUE))
}
if(length(hub_mz_list)<1){
hub_mz_list<-which(check_cor>0 & check2<0)
}
hub_mz_int<-hub_mz_list[which(mchemicaldata$mean_int_vec[hub_mz_list]==max(mchemicaldata$mean_int_vec[hub_mz_list]))[1]]
max_time_neighbors<-0
best_hub_time_mz<-hub_mz_int
for(h1 in hub_mz_list){
mz_name_hub<-paste(mchemicaldata$mz[h1],mchemicaldata$time[h1],sep="_")
hub_rt<-mchemicaldata$time[h1]
diff_rt_hubmz<-apply(mchemicaldata,1,function(k){curtime<-as.numeric(as.character(k[3]));return(abs(hub_rt-curtime))})
num_time_neighbors<-length(which(diff_rt_hubmz<=max_diff_rt))
if(num_time_neighbors>max_time_neighbors){
best_hub_time_mz<-h1
max_time_neighbors<-num_time_neighbors
}
}
#print(best_hub_time_mz)
# print(mchemicaldata)
hub_mz<-best_hub_time_mz
mz_name_hub<-paste(mchemicaldata$mz[hub_mz],mchemicaldata$time[hub_mz],sep="_")
hub_rt<-mchemicaldata$time[hub_mz]
diff_rt_hubmz<-apply(mchemicaldata,1,function(k){curtime<-as.numeric(as.character(k[3]));return(abs(hub_rt-curtime))})
#print(diff_rt_hubmz)
#print(cor_mz)
#print(hub_mz)
#print(mchemicaldata$mean_int_vec)
#print(cor_mz[hub_mz,])
#stop("sf")
if(MplusH.abundance.ratio.check==TRUE){
layer_one_associations<-which(cor_mz[hub_mz,]>=corthresh & mchemicaldata$mean_int_vec<mchemicaldata$mean_int_vec[hub_mz] & diff_rt_hubmz<=max_diff_rt)
}else{
layer_one_associations<-which(cor_mz[hub_mz,]>=corthresh & diff_rt_hubmz<=max_diff_rt)
}
second_level_associations<-{}
for(l in layer_one_associations){
second_level_associations<-c(second_level_associations,which(cor_mz[l,]>=0.7))
}
#print("layer one")
# print(layer_one_associations)
selected_mz<-c(hub_mz,layer_one_associations) #intersect(layer_one_associations,second_level_associations))
selected_mz<-unique(selected_mz)
sub_cor_mz<-cor_mz[hub_mz,which(cor_mz[hub_mz,]>=corthresh)]
#topquant_cor<-quantile(sub_cor_mz,0.9,na.rm=TRUE)[1]
if(is.na(topquant_cor)==TRUE){
topquant_cor=0
}
if(length(which(check_cor2>=0.1))>0){
mchemicaldata<-mchemicaldata[selected_mz,] #[which(cor_mz[hub_mz,]>=corthresh & check_cor2>=0.1),]
#print(mchemicaldata)
}else{
mchemicaldata<-mchemicaldata[which(cor_mz[hub_mz,]>=corthresh),]
}
# print(mchemicaldata)
#return(mchemicaldata)
mchemicaldata<-na.omit(mchemicaldata)
if(nrow(mchemicaldata)<2){
next
}
#print(mchemicaldata)
#print(nrow(mchemicaldata))
mchemicaldata<-as.data.frame(mchemicaldata)
diff_rt<-abs(min(as.numeric(mchemicaldata$time))-max(as.numeric(mchemicaldata$time)))
diff_rt<-round(diff_rt)
if(length(which(is.na(mchemicaldata$time))==TRUE)>0){
mchemicaldata<-mchemicaldata[-which(is.na(mchemicaldata$time)==TRUE),]
}
if(nrow(mchemicaldata)<2){
next
}
if(diff_rt<=max_diff_rt)
{
#print("DOING THIS")
dup_add<-which(duplicated(mchemicaldata$Adduct)==TRUE)
if(length(dup_add)>0){
dup_data<-mchemicaldata[c(dup_add),]
#mchemicaldata<-mchemicaldata[-c(dup_add),]
}
dup_mz_check<-dup_add
#print(dup_add)
#print(mchemicaldata)
if(dim(mchemicaldata)[1]>1){
#chemical_score<-3
k_power<-1
mchemicaldata$time<-as.numeric(as.character(mchemicaldata$time))
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]*\\])",replacement="")
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
#print("score 2")
#chemical_score<-2*2^length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
#change
chemical_score<-length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
#chemical_score<-chemical_score/sqrt(log2((0.5*diff_rt)+1))
#print(chemical_score)
if(good_adducts_len>0){
chemical_score<-sum(chemical_score*(10^max(as.numeric(as.character(adduct_weights[which(adduct_weights[,1]%in%cur_adducts_with_isotopes),2])))))
chemical_score<-chemical_score[1]
}
check2<-gregexpr(text=cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]\\])")
#print(chemical_score)
if(length(which(check2>0))>0){
chemical_score<-100*chemical_score
}
names(chemical_score)<-chemicalid[1]
#print(chemical_score)
if(length(which(mchemicaldata$Adduct%in%adduct_weights[,1]))>0){
fname<-paste(chemicalid,"score.txt",sep="_")
}
}
#return(list("chemical_score"=chemical_score,"filtdata"=mchemicaldata))
}
else{
#print("fixing time")
#return(mchemicaldata)
#mchemicaldata<-chem_score
mchemicaldata$Module_RTclust<-gsub(mchemicaldata$Module_RTclust,pattern="_[0-9]*",replacement="")
mchemicaldata<-cbind(mchemicaldata[,c(2:11)],mchemicaldata[,1],mchemicaldata[,c(12:14)])
colnames(mchemicaldata)<-c("mz","time","MatchCategory","theoretical.mz","chemical_ID","Name","Formula","MonoisotopicMass","Adduct","ISgroup","Module_RTclust","time.y","mean_int_vec", "MD")
#return(mchemicaldata)
mchemicaldata<-as.data.frame(mchemicaldata)
mchemicaldata$time<-as.numeric(as.character(mchemicaldata$time))
#return(mchemicaldata)
groupnumA<-unique(mchemicaldata$Module_RTclust)
mchemicaldata<-group_by_rt_histv2(mchemicaldata,time_step=1,max_diff_rt=max_diff_rt,groupnum=groupnumA)
#print("done")
top_mod_sub<-table(mchemicaldata$Module_RTclust)
top_mod_sub_names<-names(top_mod_sub)
max_top_mod<-which(top_mod_sub==max(top_mod_sub))[1]
mchemicaldata<-mchemicaldata[which(mchemicaldata$Module_RTclust==top_mod_sub_names[max_top_mod]),]
mchemicaldata<-mchemicaldata[order(mchemicaldata$mz),]
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])",replacement="")
#print(mchemicaldata)
d1<-density(mchemicaldata$time,bw=max_diff_rt,from=min(mchemicaldata$time)-0.001,to=(0.01+max(mchemicaldata$time)),na.rm=TRUE)
s1<-summary(d1$x) #mchemicaldata$time)
iqr1<-s1[5]-s1[2]
if(iqr1>max_diff_rt/2){
iqr1<-max_diff_rt/2
}
min_val<-s1[2] #-(1.5*iqr1)
max_val<-s1[5] #+(1.5*iqr1)
{
s1<-summary(mchemicaldata$time)
iqr1<-s1[5]-s1[2]
#print(s1)
min_val<-s1[2]-(1.5*iqr1)
max_val<-s1[5]+(1.5*iqr1)
#print(min_val)
#print(max_val)
if(min_val<s1[1] && max_val>s1[6]){
#min_val<-s1[1]
iqr1<-min(abs(s1[3]-s1[2]),abs(s1[3]-s1[5]))
min_val<-s1[2]-(1.5*iqr1)
max_val<-s1[5]+(1.5*iqr1)
#max_val<-s1[6]
}
#print(mchemicaldata[hub_mz_ind,])
if(min_val<s1[1]){
min_val<-s1[1]
}
if(max_val>s1[6]){
max_val<-s1[6]
}
iqr1<-min(abs(s1[3]-s1[2]),abs(s1[3]-s1[5]))
iqr1<-max(iqr1,max_diff_rt)
diff_rt<-abs(max(mchemicaldata$time)-min(mchemicaldata$time))
# print("fixed time")
# print(diff_rt)
# print(mchemicaldata)
#return(mchemicaldata)
if(nrow(mchemicaldata)<1){
next
}
if(diff_rt>2*max_diff_rt){
time_cor_groups<-sapply(list(myData1=mchemicaldata),function(x) split(x,cut(mchemicaldata$time,breaks=seq(min_val-max_diff_rt,max_val+max_diff_rt,iqr1))))
}else{
max_val<-max(mchemicaldata$time)
min_val<-min(mchemicaldata$time)
diff_rt<-abs(max(mchemicaldata$time)-min(mchemicaldata$time))
if(min_val<max_diff_rt){
#time_cor_groups<-sapply(list(myData1=mchemicaldata),function(x) split(x,cut(mchemicaldata$time,breaks=seq(0,max_val,1*max_diff_rt))))
time_cor_groups<-sapply(list(myData1=mchemicaldata),function(x) split(x,cut(mchemicaldata$time,breaks=c(0,max_val+1))))
}else{
if(diff_rt<max_diff_rt){
time_cor_groups<-sapply(list(myData1=mchemicaldata),function(x) split(x,cut(mchemicaldata$time,breaks=c(min_val-diff_rt,max_val+diff_rt,diff_rt*2))))
}else{
time_cor_groups<-sapply(list(myData1=mchemicaldata),function(x) split(x,cut(mchemicaldata$time,breaks=seq(min_val-diff_rt,max_val+diff_rt,1*max_diff_rt))))
}
}
}
}
#return(time_cor_groups)
group_sizes<-sapply(time_cor_groups,function(x){dim(as.data.frame(x))[1]})
group_ind_val<-1
group_ind_size<-1
check_reladd<-{}
check_data<-{}
if(length(which(group_sizes>1))>0){
group_ind_val<-which(group_sizes==max(group_sizes)[1])
}
group_ind_size<-max(group_sizes)[1]
if(group_ind_size<2){
k_power<-1.25
mchemicaldata<-mchemicaldata_orig[which(mchemicaldata_orig$Module_RTclust==top_mod[i]),]
mchemicaldata<-mchemicaldata[order(mchemicaldata$mz),]
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])",replacement="")
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
# chemical_score<-length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))*(1/((diff_rt*0.1)+1)^k_power)
#change
chemical_score<-length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
if(good_adducts_len>0){
chemical_score<-sum(chemical_score*(as.numeric(adduct_weights[which(adduct_weights[,1]%in%cur_adducts),2])))
}
}
good_temp<-{}
for(g1 in 1:length(group_sizes))
{
tempdata<-time_cor_groups[[g1]]
check_reladd<-which(tempdata$Adduct%in%as.character(adduct_weights[,1]))
if(length(check_reladd)>0){
good_temp<-c(good_temp,g1)
if(nrow(tempdata)>group_ind_size){
group_ind_val<-g1
group_ind_size<-nrow(tempdata)
}
}
}
if(length(which(group_sizes>1))>0)
{
temp_best_score<-(-100)
temp_best_data<-{}
for(g2 in 1:length(group_sizes)){
if(g2%in%good_temp){
mchemicaldata<-{}
mchemicaldata<-rbind(mchemicaldata,time_cor_groups[[g2]])
mchemicaldata<-as.data.frame(mchemicaldata)
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])",replacement="")
if(length(mchemicaldata)<1){
next
}
if(nrow(mchemicaldata)<1){
next
}
diff_rt<-abs(min(as.numeric(mchemicaldata$time))-max(as.numeric(mchemicaldata$time)))
diff_rt<-round(diff_rt)
#print("diff rT")
#print(diff_rt)
#print(mchemicaldata)
dup_add<-{} #which(duplicated(mchemicaldata$Adduct)==TRUE)
if(length(dup_add)>0){
dup_data<-mchemicaldata[c(dup_add),]
#mchemicaldata<-mchemicaldata[-c(dup_add),]
}
if(length(mchemicaldata)<1){
next
}
if(nrow(mchemicaldata)<1){
next
}
if(diff_rt<=max_diff_rt)
{
if(dim(mchemicaldata)[1]>1)
{
k_power<-1
mchemicaldata$time<-as.numeric(as.character(mchemicaldata$time))
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]*\\])",replacement="")
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
#print("score 3")
#chemical_score<-2*2^length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
#change
chemical_score<-length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
#chemical_score<-chemical_score/sqrt(log2((0.5*diff_rt)+1))
if(good_adducts_len>0){
#chemical_score<-chemical_score*(2^adduct_weights[which(adduct_weights[,1]%in%cur_adducts),2])
chemical_score<-sum(chemical_score*(10^max(as.numeric(as.character(adduct_weights[which(adduct_weights[,1]%in%cur_adducts_with_isotopes),2])))))
chemical_score<-chemical_score[1]
}
check2<-gregexpr(text=cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]*\\])")
if(length(which(check2>0))>0){
chemical_score<-100*chemical_score
}
}else{
chemical_score<-0
}
names(chemical_score)<-chemicalid[1]
}else{
d1<-density(mchemicaldata$time,bw=max_diff_rt,from=min(mchemicaldata$time)-0.001,to=(0.01+max(mchemicaldata$time)),na.rm=TRUE)
s1<-summary(d1$x)
iqr1<-s1[5]-s1[2]
if(iqr1>max_diff_rt/2){
iqr1<-max_diff_rt/2
}
min_val<-s1[2] #-(1.5*iqr1)
max_val<-s1[5] #+(1.5*iqr1)
if(length(which(mchemicaldata$time>=min_val & mchemicaldata$time<=max_val))>1)
{
mchemicaldata<-mchemicaldata[which(mchemicaldata$time>=(min_val-1) & mchemicaldata$time<=(max_val-1)),]
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])",replacement="")
if(dim(mchemicaldata)[1]>1)
{
k_power<-1
mchemicaldata$time<-as.numeric(as.character(mchemicaldata$time))
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]*\\])",replacement="")
# print("Setting score 3")
#print(mchemicaldata)
# chemical_score<-100*2^length(which(cur_adducts%in%adduct_weights[,1]))+1*(topquant_cor)*(1/((diff_rt*0.1)+1)^k_power) #*length(unique(cur_adducts))
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
#print("score 4")
#chemical_score<-2*2^length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
#change
chemical_score<-length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
#chemical_score<-chemical_score/sqrt(log2((0.5*diff_rt)+1))
if(good_adducts_len>0){
#chemical_score<-chemical_score*(2^adduct_weights[which(adduct_weights[,1]%in%cur_adducts),2])
chemical_score<-sum(chemical_score*(10^max(as.numeric(as.character(adduct_weights[which(adduct_weights[,1]%in%cur_adducts_with_isotopes),2])))))
chemical_score<-chemical_score[1]
}
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]*\\])",replacement="")
check2<-gregexpr(text=cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]\\])")
if(length(which(check2>0))>0){
chemical_score<-100*chemical_score
}
#*(1/((diff_rt*0.1)+1)^k_power))
}
names(chemical_score)<-chemicalid[1]
}else{
# print("Setting score 4")
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]*\\])",replacement="")
#print("score 5")
#chemical_score<-0
# chemical_score<-length(which(cur_adducts%in%adduct_weights[,1]))+1*(topquant_cor)*(1/((diff_rt*0.1)+1)^k_power)
chemical_score<-length(unique(cur_adducts))*length(which(cur_adducts%in%adduct_weights[,1]))*(1*(topquant_cor)*(1/((diff_rt*0.1)+1)^k_power))
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
#change
chemical_score<-length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
if(good_adducts_len>0){
chemical_score<-sum(chemical_score*(as.numeric(adduct_weights[which(adduct_weights[,1]%in%cur_adducts),2])))
}
names(chemical_score)<-chemicalid[1]
}
}
if(chemical_score>temp_best_score)
{
temp_best_data<-mchemicaldata
mchemicaldata<-temp_best_data
temp_best_score<-chemical_score
}
}
}
mchemicaldata<-temp_best_data
chemical_score<-temp_best_score
}
else{
#v1.4.1 removed duplicate
#dup_mz_check<-which(duplicated(mchemicaldata$Adduct)==TRUE)
# if(length(dup_mz_check)>0){
# mchemicaldata<-mchemicaldata[-c(dup_mz_check),]
#chemical_score<-0
#chemical_score<-length(which(cur_adducts%in%adduct_weights[,1]))+1*(topquant_cor)*(1/((diff_rt*0.1)+1)^k_power)
#names(chemical_score)<-chemicalid[1]
# }
if(dim(mchemicaldata)[1]>1){
diff_rt<-abs(min(as.numeric(mchemicaldata$time))-max(as.numeric(mchemicaldata$time)))
d1<-density(mchemicaldata$time,bw=max_diff_rt,from=min(mchemicaldata$time)-0.001,to=(0.01+max(mchemicaldata$time)),na.rm=TRUE)
s1<-summary(d1$x) #mchemicaldata$time)
iqr1<-s1[5]-s1[2]
if(iqr1>max_diff_rt/2){
iqr1<-max_diff_rt/2
}
min_val<-s1[2] #-(1.5*iqr1)
max_val<-s1[5] #+(1.5*iqr1)
if(length(which(mchemicaldata$time>=min_val & mchemicaldata$time<=max_val))>1)
{
mchemicaldata<-mchemicaldata[which(mchemicaldata$time>=min_val & mchemicaldata$time<=max_val),]
dup_add<-which(duplicated(mchemicaldata$Adduct)==TRUE)
if(length(dup_add)>0){
dup_data<-mchemicaldata[c(dup_add),]
#mchemicaldata<-mchemicaldata[-c(dup_add),]
}
if(dim(mchemicaldata)[1]>1)
{
k_power<-1
mchemicaldata$time<-as.numeric(as.character(mchemicaldata$time))
dup_add<-which(duplicated(mchemicaldata$Adduct)==TRUE)
if(length(dup_add)>0){
dup_data<-mchemicaldata[c(dup_add),]
#mchemicaldata<-mchemicaldata[-c(dup_add),]
}
if(length(mchemicaldata)>0){
if(nrow(mchemicaldata)>1){
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])",replacement="")
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
#print("score 6")
# chemical_score<-2*2^length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
#change
chemical_score<-length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
#chemical_score<-chemical_score/sqrt(log2((0.5*diff_rt)+1))
if(good_adducts_len>0){
chemical_score<-sum(chemical_score*(10^max(as.numeric(as.character(adduct_weights[which(adduct_weights[,1]%in%cur_adducts_with_isotopes),2])))))
chemical_score<-chemical_score[1]
}
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]*\\])",replacement="")
check2<-gregexpr(text=cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]*\\])")
if(length(which(check2>0))>0){
chemical_score<-100*chemical_score
}
}else{
chemical_score<-0
}
}else{
chemical_score<-0
}
}
names(chemical_score)<-chemicalid[1]
}else
{
dup_add<-which(duplicated(mchemicaldata$Adduct)==TRUE)
if(length(dup_add)>0){
dup_data<-mchemicaldata[c(dup_add),]
#mchemicaldata<-mchemicaldata[-c(dup_add),]
}
if(length(mchemicaldata)>0){
if(nrow(mchemicaldata)>1){
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])",replacement="")
if(diff_rt>max_diff_rt){
k_power<-3
# print("score 7")
#chemical_score<-0
#length(unique(cur_adducts))*length(which(cur_adducts%in%adduct_weights[,1]))*(1*(topquant_cor)*(1/((diff_rt*0.1)+1)^k_power))
chemical_score<-length(unique(cur_adducts))*length(which(cur_adducts%in%adduct_weights[,1]))*(1*(topquant_cor)*(1/((diff_rt*0.1)+1)^k_power))
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
#change
chemical_score<-length(unique(cur_adducts))*good_adducts_len*(1*(topquant_cor))
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
if(good_adducts_len>0){
chemical_score<-sum(chemical_score*(as.numeric(adduct_weights[which(adduct_weights[,1]%in%cur_adducts),2])))
}
}
}else{
chemical_score<-0
#chemical_score<-length(which(cur_adducts%in%adduct_weights[,1]))+1*(topquant_cor)*(1/((diff_rt*0.1)+1)^k_power)
}
}else{
chemical_score<-0
}
}
#chemical_score<-(topquant_cor)*(1/(diff_rt+1)^k_power)*length(unique(mchemicaldata$Adduct))
#print("setting score 6")
}
names(chemical_score)<-chemicalid[1]
}
names(chemical_score)<-chemicalid[1]
mchemicaldata<-mchemicaldata #[,c(1:11)]
mchemicaldata<-na.omit(mchemicaldata)
if(length(which(mchemicaldata$Adduct%in%adduct_weights[,1]))>0){
# return(list("chemical_score"=chemical_score,"filtdata"=mchemicaldata))
}
}
}
else{
#no correlation between putative adducts
#print("setting score 7")
cur_adducts_with_isotopes<-mchemicaldata$Adduct
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
#print(mchemicaldata)
if(good_adducts_len>0)
{
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]*\\])",replacement="")
max_adduct_weight<-max(as.numeric(as.character(adduct_weights[which(adduct_weights[,1]%in%cur_adducts_with_isotopes),2])))[1]
chemical_score<-((10^max_adduct_weight))
#print("score 7")
chemical_score<-chemical_score[1]
good_adduct_index<-which(adduct_weights[,2]==max_adduct_weight)
chemical_score<-chemical_score[1]
mchemicaldata<-mchemicaldata[which(cur_adducts_with_isotopes%in%adduct_weights[good_adduct_index,1]),]
if(FALSE){
if(chemical_score>best_chemical_score)
{
best_chemical_score<-chemical_score
best_conf_level<-1
best_mod_ind<-i
best_data<-mchemicaldata
}
}
}else{
#
chemical_score<-0
mchemicaldata<-mchemicaldata_orig[which(mchemicaldata_orig$Module_RTclust==top_mod[i]),]
mchemicaldata<-mchemicaldata[order(mchemicaldata$mz),]
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])",replacement="")
#next;
}
}
}
#mchemicaldata<-mchemicaldata[order(mchemicaldata$Adduct),]
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])",replacement="")
check2<-gregexpr(text=cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[0-9]*\\])")
if(length(check2)>0){
for(a1 in 1:length(check2)){
strlength<-attr(check2[[a1]],"match.length")
if(strlength[1]>(-1)){
count_abundant_form<-length(which(cur_adducts%in%cur_adducts[a1]))
if(count_abundant_form<2)
{
chemscoremat_conf_levels<-"None"
mchemicaldata<-mchemicaldata[-a1,]
}
}
}
}
#if(nrow(mchemicaldata)<1){
conf_level<-0
if(length(mchemicaldata)<1){
conf_level<-0
}else{
if(nrow(mchemicaldata)>0){
conf_level<-get_confidence_stage2(curdata=mchemicaldata,adduct_weights=adduct_weights)
conf_level<-as.numeric(as.character(conf_level))
}else{
conf_level<-0
}
}
if(length(mchemicaldata)>0){
if(nrow(mchemicaldata)>1){
diff_rt<-max(mchemicaldata$time)-min(mchemicaldata$time)
k_power=1
if(diff_rt>max_diff_rt)
{
k_power=10
}
chemical_score<-chemical_score*(1/((diff_rt*0.1)+1)^k_power)
}
}else{
chemical_score<-0
}
min_chemical_score<-100*2*(1*(corthresh))*(1/((max_diff_rt*0.1)+1)^3)
if(chemical_score>min_chemical_score){
chemical_score<-chemical_score*(conf_level^conf_level)
}else{
chemical_score<-0
}
if(length(dup_add)>0){
mchemicaldata<-rbind(mchemicaldata,dup_data)
}
if(is.na(conf_level)==TRUE){
conf_level<-0
}
if(is.na(chemical_score)==TRUE){
chemical_score<-0
}
if(chemical_score>best_chemical_score & conf_level>0) #| conf_level>=best_conf_level)
{
best_chemical_score<-chemical_score
best_conf_level<-conf_level
best_mod_ind<-i
best_data<-mchemicaldata
}else{
if(chemical_score==best_chemical_score)
{
best_chemical_score<-chemical_score
best_conf_level<-1
best_mod_ind<-c(i,best_mod_ind)
best_data<-rbind(best_data,mchemicaldata)
}
}
if(FALSE)
{
print("i is")
print(i)
print(mchemicaldata)
print(top_mod[i])
print("score is")
print(chemical_score)
print(best_chemical_score)
print("conf level")
print(conf_level)
}
}
##for loop complete
if(best_chemical_score>0){
chemical_score<-best_chemical_score
best_mod<-best_mod_ind
mchemicaldata<-best_data
names(chemical_score)<-chemicalid[1]
#return(list("chemical_score"=chemical_score,"filtdata"=mchemicaldata))
}else{
chemical_score<-0
}
}
#######add code for only correlation criteria here
#if(FALSE)
{
#if(chemical_score<=0)
#print("length is")
#print(length(which(mchemicaldata$Adduct%in%as.character(filter.by))))
if(chemical_score<=1) # || length(which(mchemicaldata$Adduct%in%as.character(filter.by)))<1)
{
mchemicaldata<-mchemicaldata_orig
cur_adducts_with_isotopes<-mchemicaldata$Adduct
cur_adducts<-gsub(cur_adducts_with_isotopes,pattern="(_\\[(\\+|\\-)[1-2]*\\])",replacement="")
good_adducts_len<-length(which(cur_adducts_with_isotopes%in%adduct_weights[,1]))
if(good_adducts_len>0)
{
max_adduct_weight<-max(as.numeric(as.character(adduct_weights[which(adduct_weights[,1]%in%cur_adducts_with_isotopes),2])))[1]
chemical_score<-((10^max_adduct_weight))
chemical_score<-chemical_score[1]-1
good_adduct_index<-which(adduct_weights[,2]==max_adduct_weight)
chemical_score<-chemical_score[1]
mchemicaldata<-mchemicaldata[which(cur_adducts_with_isotopes%in%adduct_weights[good_adduct_index,1]),]
}
}
}
if(nrow(mchemicaldata)>0){
mchemicaldata<-unique(mchemicaldata)
mzid_cur<-paste(mchemicaldata$mz,mchemicaldata$time,sep="_")
#dweight1<-degree_weights[which(mzid%in%mzid_cur),]
}else{
dweight1<-c(0)
chemical_score<-0
}
#
#print(best_chemical_score)
rm("mzid","global_cor","temp_global_cor")
return(list("chemical_score"=chemical_score,"filtdata"=mchemicaldata))
}
}
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