R/get_confidence_stage4.R
In yufree/xMSannotator: xMSannotator: R package for network based annotation of metabolomics data.
Defines functions
get_confidence_stage4
get_confidence_stage4 <- function(curdata, max_diff_rt, adduct_weights = NA,
filter.by = NA, min_ions_perchem = 1, max_isp = 5) {
curdata <- curdata[order(curdata$Adduct), ]
# return(curdata)
if (curdata$score[1] < 0.1) {
score_level <- 0
final_res <- cbind(score_level, curdata)
final_res <- as.data.frame(final_res)
# final_res$score_level<-(as.numeric(as.factor(final_res$score_level)))
# print(final_res)
return(final_res)
}
curdata_all <- curdata
cur_adducts_with_isotopes <- curdata$Adduct
cur_adducts <- gsub(cur_adducts_with_isotopes, pattern = "(_\\[(\\+|\\-)[0-9]*\\])",
replacement = "")
# cur_adducts<-gsub(cur_adducts_with_isotopes,pattern='(_\\[\\-[0-9]*\\])',replacement='')
if (is.na(adduct_weights)[1] == TRUE) {
data(adduct_table)
data(adduct_weights)
adduct_weights1 <- matrix(nrow = 2, ncol = 2, 0)
adduct_weights1[1, ] <- c("M+H", 1)
adduct_weights1[2, ] <- c("M-H", 1)
adduct_weights <- as.data.frame(adduct_weights1)
colnames(adduct_weights) <- c("Adduct", "Weight")
}
adduct_monoisot <- data.frame(cbind("M", 1, 1, 0, "-",
"S"))
colnames(adduct_monoisot) <- colnames(adduct_table)
adduct_table <- rbind(adduct_table, adduct_monoisot)
adduct_table <- adduct_table[order(adduct_table$Adduct),
]
curdata <- cbind(curdata, cur_adducts)
curdata <- merge(curdata, adduct_table, by.x = "cur_adducts",
by.y = "Adduct")
curdata <- curdata[, -c(1)]
# return(curdata)
formula_vec <- curdata$Formula
temp1 <- curdata
temp1$Module_RTclust <- gsub(temp1$Module_RTclust, pattern = "(_[0-9]*)",
replacement = "")
table_modules <- table(temp1$Module_RTclust)
rm(temp1)
module_names <- names(table_modules[which(table_modules >
0)])
chemscoremat_conf_levels <- "High"
if (length(which(adduct_table$Adduct %in% cur_adducts)) <
1) {
chemscoremat_conf_levels <- "None"
# return(chemscoremat_conf_levels)
}
if (length(unique(curdata$Adduct)) < 2 && curdata$score[1] <
10 && length(which(cur_adducts %in% filter.by)) <
1) {
chemscoremat_conf_levels <- "None"
# return(chemscoremat_conf_levels)
} else {
if (length(unique(curdata$Adduct)) < 2 && length(which(cur_adducts %in%
filter.by)) > 0) {
chemscoremat_conf_levels <- "Low"
# return(chemscoremat_conf_levels)
}
}
if (length(unique(curdata$Adduct)) < 2 && nrow(curdata) >
1) {
if (nrow(curdata) == 2) {
chemscoremat_conf_levels <- "Medium"
}
# return(chemscoremat_conf_levels)
if (length(which(cur_adducts %in% filter.by)) < 1) {
chemscoremat_conf_levels <- "None"
# return(chemscoremat_conf_levels)
} else {
curdata <- curdata[which(cur_adducts %in% filter.by),
]
score_level <- "2"
score_level <- as.numeric(as.character(score_level))
final_res <- cbind(score_level, curdata)
return(final_res)
}
}
curdata$time <- as.numeric(as.character(curdata$time))
delta_rt <- max(curdata$time) - min(curdata$time)
delta_rt <- round(delta_rt)
if (delta_rt > max_diff_rt) {
# chemscoremat_conf_levels<-'Medium'
# if(delta_rt>10){
chemscoremat_conf_levels <- "None"
# }
groupB <- group_by_rt(curdata, time_step = 3, max.rt.diff = max_diff_rt,
groupnum = "")
groupB <- groupB[order(groupB$mz), ]
cname1 <- paste(groupB$mz, groupB$time, sep = "_")
if (length(which(duplicated(cname1) == TRUE)) > 0) {
groupB <- groupB[-which(duplicated(cname1) ==
TRUE), ]
}
curdata <- curdata[order(curdata$mz), ]
# print(curdata) print(groupB)
module_clust <- groupB[, 1] #paste(curdata$module_num,groupB[,1],sep='')
curdata$Module_RTclust <- module_clust
# print('here') print(curdata)
if (length(which(adduct_weights[, 1] %in% cur_adducts)) >
0 && curdata$score[1] > 0.1) {
if (is.na(filter.by)[1] == TRUE) {
good_mod <- curdata$Module_RTclust[which(curdata$Adduct %in%
adduct_weights[, 1])]
curdata <- curdata[which(curdata$Module_RTclust %in%
good_mod), ]
t1 <- table(curdata$Module_RTclust)
t2 <- t1[which(t1 > 0)]
t2 <- t2[which(t2 == max(t2)[1])]
n1 <- names(t2)
curdata <- curdata[which(curdata$Module_RTclust ==
n1[1]), ]
delta_rt <- max(curdata$time) - min(curdata$time)
delta_rt <- round(delta_rt)
if (curdata$score[1] > 0 && nrow(curdata) >
1 && length(unique(curdata$Adduct)) > 1 &&
delta_rt < max_diff_rt) {
chemscoremat_conf_levels <- "High"
} else {
chemscoremat_conf_levels <- "Low"
}
# print('here2')
} else {
if (length(which(cur_adducts %in% filter.by)) >
0) {
good_mod <- curdata$Module_RTclust[which(curdata$Adduct %in%
filter.by)]
curdata <- curdata[which(curdata$Module_RTclust %in%
good_mod), ]
curdata <- as.data.frame(curdata)
t1 <- table(curdata$Module_RTclust)
t2 <- t1[which(t1 > 0)]
t2 <- t2[which(t2 == max(t2)[1])]
n1 <- names(t2)
curdata <- curdata[which(curdata$Module_RTclust ==
n1[1]), ]
delta_rt <- max(curdata$time) - min(curdata$time)
delta_rt <- round(delta_rt)
if (length(which(t1 > 1)) < 1) {
if (curdata$score[1] > 0 && nrow(curdata) >
1 && length(unique(curdata$Adduct)) >
1 && delta_rt < max_diff_rt && length(which(curdata$Adduct %in%
filter.by)) > 0) {
chemscoremat_conf_levels <- "High"
} else {
if (curdata$score[1] > 0 && length(which(curdata$Adduct %in%
filter.by)) > 0) {
chemscoremat_conf_levels <- "Medium"
} else {
if (curdata$score[1] > 0) {
chemscoremat_conf_levels <- "Low"
} else {
chemscoremat_conf_levels <- "None"
}
}
}
} else {
t2 <- t1[which(t1 > 0)]
t2 <- t2[which(t2 == max(t2)[1])]
n1 <- names(t2)
curdata <- curdata[which(curdata$Module_RTclust ==
n1[1]), ]
delta_rt <- max(curdata$time) - min(curdata$time)
delta_rt <- round(delta_rt)
if (curdata$score[1] > 0 && nrow(curdata) >
1 && length(unique(curdata$Adduct)) >
1 && delta_rt < max_diff_rt && length(which(curdata$Adduct %in%
filter.by)) > 0) {
chemscoremat_conf_levels <- "High"
} else {
if (curdata$score[1] > 0 && length(which(curdata$Adduct %in%
filter.by)) > 0 && delta_rt < max_diff_rt) {
chemscoremat_conf_levels <- "Medium"
} else {
if (curdata$score[1] > 0) {
chemscoremat_conf_levels <- "Low"
} else {
chemscoremat_conf_levels <- "None"
}
}
}
}
}
}
} else {
# print(length(which(adduct_weights[,1]%in%cur_adducts)))
# print(curdata$score[1])
# print('here')
chemscoremat_conf_levels <- "None"
}
module_clust <- paste(curdata$module_num, curdata$Module_RTclust,
sep = "")
curdata$Module_RTclust <- module_clust
}
curdata <- as.data.frame(curdata)
# print('here 31') print(curdata)
temp1 <- curdata
temp1$Module_RTclust <- gsub(temp1$Module_RTclust, pattern = "(_[0-9]*)",
replacement = "")
table_modules <- table(temp1$Module_RTclust)
rm(temp1)
module_names <- names(table_modules[which(table_modules >
0)])
# print('new mnames') print(module_names)
# print('OVER HERE') else
{
# change in 1.5.3
if (length(module_names) > 1 && curdata$score[1] < 10) {
chemscoremat_conf_levels <- "None"
} else {
if (length(module_names) > 1 && curdata$score[1] >
10 && length(which(cur_adducts %in% filter.by)) >
0) {
chemscoremat_conf_levels <- "Medium"
}
}
# else
{
if (nrow(curdata) < 2) {
# chemscoremat_conf_levels<-'Low'
if (length(which(cur_adducts %in% adduct_weights[,
1])) < 1) {
chemscoremat_conf_levels <- "Low"
} else {
# matches an M+H and score is greater than 10
if (curdata$score[1] > 10 && length(which(cur_adducts %in%
filter.by)) > 0) {
chemscoremat_conf_levels <- "Medium"
} else {
chemscoremat_conf_levels <- "None"
}
}
} else {
min_nummol <- min(curdata$num_molecules)
min_nummol_ind <- which(curdata$num_molecules ==
min_nummol)
# num molecules check
if (min_nummol > 1) {
chemscoremat_conf_levels <- "Low"
} else {
# Multiple molecules abundance check
check1 <- gregexpr(text = cur_adducts,
pattern = "([2-3]+M)")
if (length(check1) > 0) {
# adduct_charges<-adduct_table[which(adduct_table$Adduct%in%cur_adducts),2]
min_mol <- min(curdata$num_molecules)
min_mol_ind <- which(curdata$num_molecules ==
min_mol)
max_int_min_mol <- max(curdata$mean_int_vec[min_mol_ind])
# max_int_min_charge<-max(curdata$mean_int_vec[min_mol_ind])
bad_ind_status <- rep(0, length(check1))
min_mol <- min(adduct_table[which(adduct_table$Adduct %in%
cur_adducts), 2])
# print('Max int') print(min_mol) print(max_int_min_mol)
if (min_mol < 2) {
# check pattern of each adduct
for (a1 in 1:length(check1)) {
strlength <- attr(check1[[a1]], "match.length")
# print(strlength)
if (strlength[1] > (-1)) {
# if(min_charge<2)
{
abund_ratio <- curdata$mean_int_vec[a1]/max_int_min_mol
# print('abund ratio is') print(abund_ratio)
if (is.na(abund_ratio)[1] == FALSE) {
if (abund_ratio[1] > 1) {
bad_ind_status[a1] <- 1
if (chemscoremat_conf_levels[1] ==
"High") {
chemscoremat_conf_levels <- "Medium"
} else {
chemscoremat_conf_levels <- "Low"
}
}
} else {
chemscoremat_conf_levels <- "Low"
bad_ind_status[a1] <- 1
}
}
}
}
if (length(which(bad_ind_status ==
1)) > 0) {
# print(curdata) print(bad_ind_status)
bad_adducts <- cur_adducts[which(bad_ind_status ==
1)]
# curdata<-curdata[-which(bad_ind_status==1),]
# curdata<-curdata[-which(cur_adducts%in%bad_adducts),]
# print(curdata)
}
if (length(nrow(curdata) > 0)) {
cur_adducts_with_isotopes <- curdata$Adduct
# cur_adducts<-gsub(cur_adducts_with_isotopes,pattern='(_\\[\\+[0-9]\\])',replacement='')
# cur_adducts<-gsub(cur_adducts_with_isotopes,pattern='(_\\[\\+[0-9]*\\])',replacement='')
cur_adducts <- gsub(cur_adducts_with_isotopes,
pattern = "(_\\[(\\+|\\-)[0-9]*\\])",
replacement = "")
# cur_adducts<-gsub(cur_adducts,pattern='(_\\[\\-[0-9]*\\])',replacement='')
} else {
# print('here1')
chemscoremat_conf_levels <- "None"
}
} else {
# print('here1')
chemscoremat_conf_levels <- "Low"
}
# Multiply charged ions if(FALSE)
{
adduct_charges <- curdata$charge # adduct_table[which(adduct_table$Adduct%in%cur_adducts),3]
min_charge <- min(curdata$charge)
min_charge_ind <- which(curdata$charge ==
min_charge)
high_charge_ind <- which(curdata$charge >
1)
max_int_min_charge <- max(curdata$mean_int_vec) #[min_charge_ind])
if (length(high_charge_ind) > 0) {
abund_ratio_min_maxcharge <- max(curdata$mean_int_vec[min_charge_ind])[1]/max(curdata$mean_int_vec[high_charge_ind])[1]
if ((abund_ratio_min_maxcharge <
1)) {
chemscoremat_conf_levels <- "Low"
}
}
bad_ind_status <- rep(1, length(check1))
if ((min_charge > 1)) {
chemscoremat_conf_levels <- "Low"
}
}
# isotope based check for +1 and +2 to make sure that the
# abundant form is present
check2 <- gregexpr(text = cur_adducts_with_isotopes,
pattern = "(_\\[(\\+|\\-)[0-9]*\\])")
if (length(check2) > 0) {
for (a1 in 1:length(check2)) {
strlength <- attr(check2[[a1]], "match.length")
if (strlength[1] > (-1)) {
count_abundant_form <- length(which(cur_adducts %in%
cur_adducts[a1]))
if (count_abundant_form < 2) {
# print('here')
# chemscoremat_conf_levels<-'None'
curdata <- curdata[-c(a1), ]
}
}
}
}
cur_adducts_with_isotopes <- curdata$Adduct
# cur_adducts<-gsub(cur_adducts_with_isotopes,pattern='(_\\[\\+[0-9]\\])',replacement='')
# cur_adducts<-gsub(cur_adducts_with_isotopes,pattern='(_\\[\\+[0-9]*\\])',replacement='')
cur_adducts <- gsub(cur_adducts_with_isotopes,
pattern = "(_\\[(\\+|\\-)[0-9]*\\])",
replacement = "")
formula_vec <- curdata$Formula
curformula <- as.character(formula_vec[1])
# check2<-gregexpr(text=curformula,pattern='(_\\[\\+[3]\\])')
# #M+H+2 print('HERE') print('here')
# print(chemscoremat_conf_levels) print(curdata)
if (FALSE) {
check2 <- gregexpr(text = cur_adducts_with_isotopes,
pattern = "(_\\[(\\+|\\-)[0-9]*\\])") #M+H_2
curformula <- gsub(curformula, pattern = "Sr",
replacement = "")
curformula <- gsub(curformula, pattern = "Sn",
replacement = "")
curformula <- gsub(curformula, pattern = "Se",
replacement = "")
curformula <- gsub(curformula, pattern = "Sc",
replacement = "")
curformula <- gsub(curformula, pattern = "Sm",
replacement = "")
curformula <- gsub(curformula, pattern = "(_\\[(\\+|\\-)[2]*\\])",
replacement = "")
if (length(check2) > 0) {
for (a1 in 1:length(check2)) {
strlength <- attr(check2[[a1]],
"match.length")
if (strlength[1] > (-1)) {
numchlorine <- check_element(curformula,
"Cl")
numsulphur <- check_element(curformula,
"S")
numbromine <- check_element(curformula,
"Br")
max_isp_count <- max(numchlorine,
numsulphur, numbromine)
if (is.na(max_isp_count) == TRUE |
max_isp_count == 0) {
# chemscoremat_conf_levels<-'None'
curdata <- curdata[-c(a1),
]
} else {
if (max_isp_count < 1) {
# chemscoremat_conf_levels<-'None'
curdata <- curdata[-c(a1),
]
}
}
}
}
}
}
}
}
}
}
}
formula_vec <- curdata$Formula
curformula <- as.character(formula_vec[1])
curformula <- gsub(curformula, pattern = "Ca", replacement = "")
curformula <- gsub(curformula, pattern = "Cl", replacement = "")
curformula <- gsub(curformula, pattern = "Cd", replacement = "")
curformula <- gsub(curformula, pattern = "Cr", replacement = "")
numcarbons <- check_element(curformula, "C")
if (numcarbons[1] < 1) {
chemscoremat_conf_levels <- "None"
}
if (length(unique(curdata$Adduct)) < 2 && nrow(curdata) >
1) {
if (nrow(curdata) == 2) {
chemscoremat_conf_levels <- "Medium"
}
# return(chemscoremat_conf_levels)
if (length(which(cur_adducts %in% filter.by)) < 1) {
chemscoremat_conf_levels <- "None"
return(chemscoremat_conf_levels)
}
} else {
if (length(unique(curdata$Adduct)) < 2 && curdata$score[1] <
10 && length(which(cur_adducts %in% filter.by)) <
1) {
chemscoremat_conf_levels <- "None"
# return(chemscoremat_conf_levels)
} else {
if (length(unique(curdata$Adduct)) < 2 && curdata$score[1] >
10 && length(which(cur_adducts %in% filter.by)) >
0) {
chemscoremat_conf_levels <- "Medium"
# return(chemscoremat_conf_levels)
} else {
if (length(unique(curdata$Adduct)) < 2 &&
curdata$score[1] < 10 && length(which(cur_adducts %in%
filter.by)) > 0) {
chemscoremat_conf_levels <- "Low"
# return(chemscoremat_conf_levels)
}
}
}
}
if (nrow(curdata) < 1) {
score_level <- 0
# curdata<-c(-1)
curdata <- curdata_all
} else {
# 3: High 2: medium 1: Low 0: None
score_level <- as.character(chemscoremat_conf_levels)
score_level <- gsub(score_level, pattern = "High",
replacement = "3")
score_level <- gsub(score_level, pattern = "Medium",
replacement = "2")
score_level <- gsub(score_level, pattern = "Low",
replacement = "1")
score_level <- gsub(score_level, pattern = "None",
replacement = "0")
}
if (is.na(score_level[1]) == TRUE) {
stop(curdata)
}
score_level <- as.numeric(as.character(score_level))
final_res <- cbind(score_level, curdata)
# print('curdata') print(curdata) print('score')
# print(score_level)
final_res <- as.data.frame(final_res)
# final_res$score_level<-(as.numeric(as.factor(final_res$score_level)))
# print(final_res) return(final_res)
if (length(which(is.na(final_res$score_level) == TRUE)) >
0) {
final_res$score_level <- replace(final_res$score_level,
which(is.na(final_res$score_level) == TRUE),
0)
}
# final_res$score_level<-replace(final_res$score_level,which(final_res$score_level<1),0)
num_uniq_adducts <- length(unique(curdata$Adduct))
uniq_adducts <- unique(curdata$Adduct)
# num_good_adducts<-length(which(uniq_adducts%in%adduct_weights[,1]))
num_good_adducts <- length(which(uniq_adducts %in% filter.by))
if (num_good_adducts > 0) {
final_res$score <- final_res$score * num_good_adducts
} else {
final_res$score <- final_res$score * (0)
}
# {
# print(final_res) stop('Pyridoxine') stop('Methionine')
# }
# final_res$score_level<-as.numeric(as.character(final_res$score_level))
if (nrow(final_res) < min_ions_perchem) {
final_res$score_level <- 0 #max(1,final_res$score_level)
}
# print(final_res)
final_res <- as.data.frame(final_res)
rm(list = c("curdata_all", "cur_adducts_with_isotopes",
"cur_adducts", "adduct_monoisot", "curdata", "temp1",
"table_modules", "chemscoremat_conf_levels", "score_level",
"groupB", "good_mod", "module_clust", "uniq_adducts",
"num_good_adducts", "num_uniq_adducts"))
return(final_res)
}
yufree/xMSannotator documentation built on Oct. 31, 2022, 12:20 a.m.
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Defines functions get_confidence_stage4
get_confidence_stage4 <- function(curdata, max_diff_rt, adduct_weights = NA,
filter.by = NA, min_ions_perchem = 1, max_isp = 5) {
curdata <- curdata[order(curdata$Adduct), ]
# return(curdata)
if (curdata$score[1] < 0.1) {
score_level <- 0
final_res <- cbind(score_level, curdata)
final_res <- as.data.frame(final_res)
# final_res$score_level<-(as.numeric(as.factor(final_res$score_level)))
# print(final_res)
return(final_res)
}
curdata_all <- curdata
cur_adducts_with_isotopes <- curdata$Adduct
cur_adducts <- gsub(cur_adducts_with_isotopes, pattern = "(_\\[(\\+|\\-)[0-9]*\\])",
replacement = "")
# cur_adducts<-gsub(cur_adducts_with_isotopes,pattern='(_\\[\\-[0-9]*\\])',replacement='')
if (is.na(adduct_weights)[1] == TRUE) {
data(adduct_table)
data(adduct_weights)
adduct_weights1 <- matrix(nrow = 2, ncol = 2, 0)
adduct_weights1[1, ] <- c("M+H", 1)
adduct_weights1[2, ] <- c("M-H", 1)
adduct_weights <- as.data.frame(adduct_weights1)
colnames(adduct_weights) <- c("Adduct", "Weight")
}
adduct_monoisot <- data.frame(cbind("M", 1, 1, 0, "-",
"S"))
colnames(adduct_monoisot) <- colnames(adduct_table)
adduct_table <- rbind(adduct_table, adduct_monoisot)
adduct_table <- adduct_table[order(adduct_table$Adduct),
]
curdata <- cbind(curdata, cur_adducts)
curdata <- merge(curdata, adduct_table, by.x = "cur_adducts",
by.y = "Adduct")
curdata <- curdata[, -c(1)]
# return(curdata)
formula_vec <- curdata$Formula
temp1 <- curdata
temp1$Module_RTclust <- gsub(temp1$Module_RTclust, pattern = "(_[0-9]*)",
replacement = "")
table_modules <- table(temp1$Module_RTclust)
rm(temp1)
module_names <- names(table_modules[which(table_modules >
0)])
chemscoremat_conf_levels <- "High"
if (length(which(adduct_table$Adduct %in% cur_adducts)) <
1) {
chemscoremat_conf_levels <- "None"
# return(chemscoremat_conf_levels)
}
if (length(unique(curdata$Adduct)) < 2 && curdata$score[1] <
10 && length(which(cur_adducts %in% filter.by)) <
1) {
chemscoremat_conf_levels <- "None"
# return(chemscoremat_conf_levels)
} else {
if (length(unique(curdata$Adduct)) < 2 && length(which(cur_adducts %in%
filter.by)) > 0) {
chemscoremat_conf_levels <- "Low"
# return(chemscoremat_conf_levels)
}
}
if (length(unique(curdata$Adduct)) < 2 && nrow(curdata) >
1) {
if (nrow(curdata) == 2) {
chemscoremat_conf_levels <- "Medium"
}
# return(chemscoremat_conf_levels)
if (length(which(cur_adducts %in% filter.by)) < 1) {
chemscoremat_conf_levels <- "None"
# return(chemscoremat_conf_levels)
} else {
curdata <- curdata[which(cur_adducts %in% filter.by),
]
score_level <- "2"
score_level <- as.numeric(as.character(score_level))
final_res <- cbind(score_level, curdata)
return(final_res)
}
}
curdata$time <- as.numeric(as.character(curdata$time))
delta_rt <- max(curdata$time) - min(curdata$time)
delta_rt <- round(delta_rt)
if (delta_rt > max_diff_rt) {
# chemscoremat_conf_levels<-'Medium'
# if(delta_rt>10){
chemscoremat_conf_levels <- "None"
# }
groupB <- group_by_rt(curdata, time_step = 3, max.rt.diff = max_diff_rt,
groupnum = "")
groupB <- groupB[order(groupB$mz), ]
cname1 <- paste(groupB$mz, groupB$time, sep = "_")
if (length(which(duplicated(cname1) == TRUE)) > 0) {
groupB <- groupB[-which(duplicated(cname1) ==
TRUE), ]
}
curdata <- curdata[order(curdata$mz), ]
# print(curdata) print(groupB)
module_clust <- groupB[, 1] #paste(curdata$module_num,groupB[,1],sep='')
curdata$Module_RTclust <- module_clust
# print('here') print(curdata)
if (length(which(adduct_weights[, 1] %in% cur_adducts)) >
0 && curdata$score[1] > 0.1) {
if (is.na(filter.by)[1] == TRUE) {
good_mod <- curdata$Module_RTclust[which(curdata$Adduct %in%
adduct_weights[, 1])]
curdata <- curdata[which(curdata$Module_RTclust %in%
good_mod), ]
t1 <- table(curdata$Module_RTclust)
t2 <- t1[which(t1 > 0)]
t2 <- t2[which(t2 == max(t2)[1])]
n1 <- names(t2)
curdata <- curdata[which(curdata$Module_RTclust ==
n1[1]), ]
delta_rt <- max(curdata$time) - min(curdata$time)
delta_rt <- round(delta_rt)
if (curdata$score[1] > 0 && nrow(curdata) >
1 && length(unique(curdata$Adduct)) > 1 &&
delta_rt < max_diff_rt) {
chemscoremat_conf_levels <- "High"
} else {
chemscoremat_conf_levels <- "Low"
}
# print('here2')
} else {
if (length(which(cur_adducts %in% filter.by)) >
0) {
good_mod <- curdata$Module_RTclust[which(curdata$Adduct %in%
filter.by)]
curdata <- curdata[which(curdata$Module_RTclust %in%
good_mod), ]
curdata <- as.data.frame(curdata)
t1 <- table(curdata$Module_RTclust)
t2 <- t1[which(t1 > 0)]
t2 <- t2[which(t2 == max(t2)[1])]
n1 <- names(t2)
curdata <- curdata[which(curdata$Module_RTclust ==
n1[1]), ]
delta_rt <- max(curdata$time) - min(curdata$time)
delta_rt <- round(delta_rt)
if (length(which(t1 > 1)) < 1) {
if (curdata$score[1] > 0 && nrow(curdata) >
1 && length(unique(curdata$Adduct)) >
1 && delta_rt < max_diff_rt && length(which(curdata$Adduct %in%
filter.by)) > 0) {
chemscoremat_conf_levels <- "High"
} else {
if (curdata$score[1] > 0 && length(which(curdata$Adduct %in%
filter.by)) > 0) {
chemscoremat_conf_levels <- "Medium"
} else {
if (curdata$score[1] > 0) {
chemscoremat_conf_levels <- "Low"
} else {
chemscoremat_conf_levels <- "None"
}
}
}
} else {
t2 <- t1[which(t1 > 0)]
t2 <- t2[which(t2 == max(t2)[1])]
n1 <- names(t2)
curdata <- curdata[which(curdata$Module_RTclust ==
n1[1]), ]
delta_rt <- max(curdata$time) - min(curdata$time)
delta_rt <- round(delta_rt)
if (curdata$score[1] > 0 && nrow(curdata) >
1 && length(unique(curdata$Adduct)) >
1 && delta_rt < max_diff_rt && length(which(curdata$Adduct %in%
filter.by)) > 0) {
chemscoremat_conf_levels <- "High"
} else {
if (curdata$score[1] > 0 && length(which(curdata$Adduct %in%
filter.by)) > 0 && delta_rt < max_diff_rt) {
chemscoremat_conf_levels <- "Medium"
} else {
if (curdata$score[1] > 0) {
chemscoremat_conf_levels <- "Low"
} else {
chemscoremat_conf_levels <- "None"
}
}
}
}
}
}
} else {
# print(length(which(adduct_weights[,1]%in%cur_adducts)))
# print(curdata$score[1])
# print('here')
chemscoremat_conf_levels <- "None"
}
module_clust <- paste(curdata$module_num, curdata$Module_RTclust,
sep = "")
curdata$Module_RTclust <- module_clust
}
curdata <- as.data.frame(curdata)
# print('here 31') print(curdata)
temp1 <- curdata
temp1$Module_RTclust <- gsub(temp1$Module_RTclust, pattern = "(_[0-9]*)",
replacement = "")
table_modules <- table(temp1$Module_RTclust)
rm(temp1)
module_names <- names(table_modules[which(table_modules >
0)])
# print('new mnames') print(module_names)
# print('OVER HERE') else
{
# change in 1.5.3
if (length(module_names) > 1 && curdata$score[1] < 10) {
chemscoremat_conf_levels <- "None"
} else {
if (length(module_names) > 1 && curdata$score[1] >
10 && length(which(cur_adducts %in% filter.by)) >
0) {
chemscoremat_conf_levels <- "Medium"
}
}
# else
{
if (nrow(curdata) < 2) {
# chemscoremat_conf_levels<-'Low'
if (length(which(cur_adducts %in% adduct_weights[,
1])) < 1) {
chemscoremat_conf_levels <- "Low"
} else {
# matches an M+H and score is greater than 10
if (curdata$score[1] > 10 && length(which(cur_adducts %in%
filter.by)) > 0) {
chemscoremat_conf_levels <- "Medium"
} else {
chemscoremat_conf_levels <- "None"
}
}
} else {
min_nummol <- min(curdata$num_molecules)
min_nummol_ind <- which(curdata$num_molecules ==
min_nummol)
# num molecules check
if (min_nummol > 1) {
chemscoremat_conf_levels <- "Low"
} else {
# Multiple molecules abundance check
check1 <- gregexpr(text = cur_adducts,
pattern = "([2-3]+M)")
if (length(check1) > 0) {
# adduct_charges<-adduct_table[which(adduct_table$Adduct%in%cur_adducts),2]
min_mol <- min(curdata$num_molecules)
min_mol_ind <- which(curdata$num_molecules ==
min_mol)
max_int_min_mol <- max(curdata$mean_int_vec[min_mol_ind])
# max_int_min_charge<-max(curdata$mean_int_vec[min_mol_ind])
bad_ind_status <- rep(0, length(check1))
min_mol <- min(adduct_table[which(adduct_table$Adduct %in%
cur_adducts), 2])
# print('Max int') print(min_mol) print(max_int_min_mol)
if (min_mol < 2) {
# check pattern of each adduct
for (a1 in 1:length(check1)) {
strlength <- attr(check1[[a1]], "match.length")
# print(strlength)
if (strlength[1] > (-1)) {
# if(min_charge<2)
{
abund_ratio <- curdata$mean_int_vec[a1]/max_int_min_mol
# print('abund ratio is') print(abund_ratio)
if (is.na(abund_ratio)[1] == FALSE) {
if (abund_ratio[1] > 1) {
bad_ind_status[a1] <- 1
if (chemscoremat_conf_levels[1] ==
"High") {
chemscoremat_conf_levels <- "Medium"
} else {
chemscoremat_conf_levels <- "Low"
}
}
} else {
chemscoremat_conf_levels <- "Low"
bad_ind_status[a1] <- 1
}
}
}
}
if (length(which(bad_ind_status ==
1)) > 0) {
# print(curdata) print(bad_ind_status)
bad_adducts <- cur_adducts[which(bad_ind_status ==
1)]
# curdata<-curdata[-which(bad_ind_status==1),]
# curdata<-curdata[-which(cur_adducts%in%bad_adducts),]
# print(curdata)
}
if (length(nrow(curdata) > 0)) {
cur_adducts_with_isotopes <- curdata$Adduct
# cur_adducts<-gsub(cur_adducts_with_isotopes,pattern='(_\\[\\+[0-9]\\])',replacement='')
# cur_adducts<-gsub(cur_adducts_with_isotopes,pattern='(_\\[\\+[0-9]*\\])',replacement='')
cur_adducts <- gsub(cur_adducts_with_isotopes,
pattern = "(_\\[(\\+|\\-)[0-9]*\\])",
replacement = "")
# cur_adducts<-gsub(cur_adducts,pattern='(_\\[\\-[0-9]*\\])',replacement='')
} else {
# print('here1')
chemscoremat_conf_levels <- "None"
}
} else {
# print('here1')
chemscoremat_conf_levels <- "Low"
}
# Multiply charged ions if(FALSE)
{
adduct_charges <- curdata$charge # adduct_table[which(adduct_table$Adduct%in%cur_adducts),3]
min_charge <- min(curdata$charge)
min_charge_ind <- which(curdata$charge ==
min_charge)
high_charge_ind <- which(curdata$charge >
1)
max_int_min_charge <- max(curdata$mean_int_vec) #[min_charge_ind])
if (length(high_charge_ind) > 0) {
abund_ratio_min_maxcharge <- max(curdata$mean_int_vec[min_charge_ind])[1]/max(curdata$mean_int_vec[high_charge_ind])[1]
if ((abund_ratio_min_maxcharge <
1)) {
chemscoremat_conf_levels <- "Low"
}
}
bad_ind_status <- rep(1, length(check1))
if ((min_charge > 1)) {
chemscoremat_conf_levels <- "Low"
}
}
# isotope based check for +1 and +2 to make sure that the
# abundant form is present
check2 <- gregexpr(text = cur_adducts_with_isotopes,
pattern = "(_\\[(\\+|\\-)[0-9]*\\])")
if (length(check2) > 0) {
for (a1 in 1:length(check2)) {
strlength <- attr(check2[[a1]], "match.length")
if (strlength[1] > (-1)) {
count_abundant_form <- length(which(cur_adducts %in%
cur_adducts[a1]))
if (count_abundant_form < 2) {
# print('here')
# chemscoremat_conf_levels<-'None'
curdata <- curdata[-c(a1), ]
}
}
}
}
cur_adducts_with_isotopes <- curdata$Adduct
# cur_adducts<-gsub(cur_adducts_with_isotopes,pattern='(_\\[\\+[0-9]\\])',replacement='')
# cur_adducts<-gsub(cur_adducts_with_isotopes,pattern='(_\\[\\+[0-9]*\\])',replacement='')
cur_adducts <- gsub(cur_adducts_with_isotopes,
pattern = "(_\\[(\\+|\\-)[0-9]*\\])",
replacement = "")
formula_vec <- curdata$Formula
curformula <- as.character(formula_vec[1])
# check2<-gregexpr(text=curformula,pattern='(_\\[\\+[3]\\])')
# #M+H+2 print('HERE') print('here')
# print(chemscoremat_conf_levels) print(curdata)
if (FALSE) {
check2 <- gregexpr(text = cur_adducts_with_isotopes,
pattern = "(_\\[(\\+|\\-)[0-9]*\\])") #M+H_2
curformula <- gsub(curformula, pattern = "Sr",
replacement = "")
curformula <- gsub(curformula, pattern = "Sn",
replacement = "")
curformula <- gsub(curformula, pattern = "Se",
replacement = "")
curformula <- gsub(curformula, pattern = "Sc",
replacement = "")
curformula <- gsub(curformula, pattern = "Sm",
replacement = "")
curformula <- gsub(curformula, pattern = "(_\\[(\\+|\\-)[2]*\\])",
replacement = "")
if (length(check2) > 0) {
for (a1 in 1:length(check2)) {
strlength <- attr(check2[[a1]],
"match.length")
if (strlength[1] > (-1)) {
numchlorine <- check_element(curformula,
"Cl")
numsulphur <- check_element(curformula,
"S")
numbromine <- check_element(curformula,
"Br")
max_isp_count <- max(numchlorine,
numsulphur, numbromine)
if (is.na(max_isp_count) == TRUE |
max_isp_count == 0) {
# chemscoremat_conf_levels<-'None'
curdata <- curdata[-c(a1),
]
} else {
if (max_isp_count < 1) {
# chemscoremat_conf_levels<-'None'
curdata <- curdata[-c(a1),
]
}
}
}
}
}
}
}
}
}
}
}
formula_vec <- curdata$Formula
curformula <- as.character(formula_vec[1])
curformula <- gsub(curformula, pattern = "Ca", replacement = "")
curformula <- gsub(curformula, pattern = "Cl", replacement = "")
curformula <- gsub(curformula, pattern = "Cd", replacement = "")
curformula <- gsub(curformula, pattern = "Cr", replacement = "")
numcarbons <- check_element(curformula, "C")
if (numcarbons[1] < 1) {
chemscoremat_conf_levels <- "None"
}
if (length(unique(curdata$Adduct)) < 2 && nrow(curdata) >
1) {
if (nrow(curdata) == 2) {
chemscoremat_conf_levels <- "Medium"
}
# return(chemscoremat_conf_levels)
if (length(which(cur_adducts %in% filter.by)) < 1) {
chemscoremat_conf_levels <- "None"
return(chemscoremat_conf_levels)
}
} else {
if (length(unique(curdata$Adduct)) < 2 && curdata$score[1] <
10 && length(which(cur_adducts %in% filter.by)) <
1) {
chemscoremat_conf_levels <- "None"
# return(chemscoremat_conf_levels)
} else {
if (length(unique(curdata$Adduct)) < 2 && curdata$score[1] >
10 && length(which(cur_adducts %in% filter.by)) >
0) {
chemscoremat_conf_levels <- "Medium"
# return(chemscoremat_conf_levels)
} else {
if (length(unique(curdata$Adduct)) < 2 &&
curdata$score[1] < 10 && length(which(cur_adducts %in%
filter.by)) > 0) {
chemscoremat_conf_levels <- "Low"
# return(chemscoremat_conf_levels)
}
}
}
}
if (nrow(curdata) < 1) {
score_level <- 0
# curdata<-c(-1)
curdata <- curdata_all
} else {
# 3: High 2: medium 1: Low 0: None
score_level <- as.character(chemscoremat_conf_levels)
score_level <- gsub(score_level, pattern = "High",
replacement = "3")
score_level <- gsub(score_level, pattern = "Medium",
replacement = "2")
score_level <- gsub(score_level, pattern = "Low",
replacement = "1")
score_level <- gsub(score_level, pattern = "None",
replacement = "0")
}
if (is.na(score_level[1]) == TRUE) {
stop(curdata)
}
score_level <- as.numeric(as.character(score_level))
final_res <- cbind(score_level, curdata)
# print('curdata') print(curdata) print('score')
# print(score_level)
final_res <- as.data.frame(final_res)
# final_res$score_level<-(as.numeric(as.factor(final_res$score_level)))
# print(final_res) return(final_res)
if (length(which(is.na(final_res$score_level) == TRUE)) >
0) {
final_res$score_level <- replace(final_res$score_level,
which(is.na(final_res$score_level) == TRUE),
0)
}
# final_res$score_level<-replace(final_res$score_level,which(final_res$score_level<1),0)
num_uniq_adducts <- length(unique(curdata$Adduct))
uniq_adducts <- unique(curdata$Adduct)
# num_good_adducts<-length(which(uniq_adducts%in%adduct_weights[,1]))
num_good_adducts <- length(which(uniq_adducts %in% filter.by))
if (num_good_adducts > 0) {
final_res$score <- final_res$score * num_good_adducts
} else {
final_res$score <- final_res$score * (0)
}
# {
# print(final_res) stop('Pyridoxine') stop('Methionine')
# }
# final_res$score_level<-as.numeric(as.character(final_res$score_level))
if (nrow(final_res) < min_ions_perchem) {
final_res$score_level <- 0 #max(1,final_res$score_level)
}
# print(final_res)
final_res <- as.data.frame(final_res)
rm(list = c("curdata_all", "cur_adducts_with_isotopes",
"cur_adducts", "adduct_monoisot", "curdata", "temp1",
"table_modules", "chemscoremat_conf_levels", "score_level",
"groupB", "good_mod", "module_clust", "uniq_adducts",
"num_good_adducts", "num_uniq_adducts"))
return(final_res)
}
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