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Read_Entry_Function.R
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Read_Entry_Function.R
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# Function for reading one entry of the Main Data
# Input: One entry of the table + additional info for the study
# Output: DataFrame to be rbind in the main dataset
# If the entry is from the macroscopic column or the organ weight column,target is not NA
read.entry <- function(entry, RO, StudyId, Species,type, Duration, Dose, Dose_interv, target=NA) {
# Define all possible options for every category
Reversibility_Values=c("r", "tr", "nr", "ap_r", "na","r_tr")
Severity_Values=c("minimal", "mild", "slight", "moderate","marked","severe")
Second_level_info_Values=c("immunogenicity", "secondary", "stress")
#Create the empty dataFrame
if (any(is.na(target))) {
df=data.frame(identifier=character(),
study_id=character(),
species=character(),
type=character(),
duration=character(),
dose=character(),
dose_interval=character(),
severity=character(),
description=character(),
adversity=character(),
reversibility=character(),
extra_info=character(),
stringsAsFactors = FALSE)
}else {
df=data.frame(identifier=character(),
study_id=character(),
species=character(),
type=character(),
duration=character(),
dose=character(),
dose_interval=character(),
severity=character(),
description=character(),
target=character(),
adversity=character(),
reversibility=character(),
extra_info=character(),
stringsAsFactors = FALSE)
}
#Split the enrty into the different findings and delete uneccesary gaps in the beginning and the end of each finding
findings_vector=unlist(strsplit(entry, ","))
findings_vector=as.character(sapply(findings_vector,trimws))
# If target is not NA, split the targets and delete uneccesary gaps in the beginning and the end of each target organ
if (!any(is.na(target))) {
target_organs=unlist(strsplit(target,","))
target_organs=as.character(sapply(target_organs,trimws))
}
#Define number of findings
numb_find=length(findings_vector)
#Start breaking each of the findings
for (i in 1:numb_find) {
#Define one specific finding
finding=findings_vector[i]
#Split the entries in the finding and delete uneccessary spaces
finding=unlist(strsplit(finding,"[-,/]"))
finding=as.character(sapply(finding,trimws))
#Start the row-entry in the dataframe
df_row=c(RO, StudyId, Species,type, Duration, Dose, Dose_interv)
#Define Adversity
index=1
if (finding[index]=="ayes") {
adversity="yes"
index=index+1
}else if (finding[index]=="yes") {
adversity="no"
index=index+1
} else {
print(paste("Error in adversity at study", StudyId,"in the dose", Dose ))
}
#Define Severity
if (finding[index] %in% Severity_Values) {
severity=finding[index]
index=index+1
}else {
severity=NA
}
#Define Description
description=finding[index]
index=index+1
#Define Reversibility
if (finding[index] %in% Reversibility_Values){
if (finding[index]=="r") {
reversibility="Reversible"
} else if (finding[index]=="nr") {
reversibility="Not_Reversible"
} else if (finding[index]=="ap_r") {
reversibility="Appeared_in_Recovery"
} else if (finding[index]=="tr") {
reversibility="Trend_Recovery"
} else if (finding[index]=="na") {
reversibility=NA
} else if (finding[index]=="r_tr") {
reversibility="Trend_Recovery_or_Recovery"
}
index=index+1
} else {
print(paste("Error in reversibility at study", StudyId,"in the dose", Dose ))
}
#Define extra_info
if (index==length(finding)) {
extra_info=finding[index]
}else{
extra_info=NA
}
# Define target if exist
if (!any(is.na(target))) {
finding_target=target_organs[i]
}
# Combine everything into a new row of the df
if (any(is.na(target))) {
df_row= append(df_row,c(severity,description,adversity,reversibility,extra_info))
}else {
df_row= append(df_row,c(severity,description,finding_target,adversity,reversibility,extra_info))
}
#Add it to the df dataframe
df_row=data.frame(t(df_row), stringsAsFactors = FALSE)
names(df_row)=names(df)
df=rbind(df,df_row)
rm(df_row)
}
return(df)
}