Applying a label depending on which condition is met using R - r

Question

I would like to use a simple R function where the contents of a specified data frame column are read row by row, then depending on the value, a string is applied to that row in a new column.
So far, I've tried to use a combination of loops and generating individual columns which were combined later. However, I cannot seem to get the syntax right.
The input looks like this:
head(data,10)
# A tibble: 10 x 5
Patient T1Score T2Score T3Score T4Score
<dbl> <dbl> <dbl> <dbl> <dbl>
1 3 96.4 75 80.4 82.1
2 5 100 85.7 53.6 55.4
3 6 82.1 85.7 NA NA
4 7 82.1 85.7 60.7 28.6
5 8 100 76.8 64.3 57.7
6 10 46.4 57.1 NA 75
7 11 71.4 NA NA NA
8 12 98.2 92.9 85.7 82.1
9 13 78.6 89.3 37.5 42.9
10 14 89.3 100 64.3 87.5
and the function I have written looks like this:
minMax<-function(x){
#make an empty data frame for the output to go
output<-data.frame()
#making sure the rest of the commands only look at what I want them to look at in the input object
a<-x[2:5]
#here I'm gathering the columns necessary to perform the calculation
minValue<-apply(a,1,min,na.rm=T)
maxValue<-apply(a,1,max,na.rm=T)
tempdf<-as.data.frame((cbind(minValue,maxValue)))
Difference<-tempdf$maxValue-tempdf$minValue
referenceValue<-ave(Difference)
referenceValue<-referenceValue[1]
#quick aside to make the first two thirds of the output file
output<-as.data.frame((cbind(x[1],Difference)))
#Now I need to define the class based on the referenceValue, and here is where I run into trouble.
apply(output, 1, FUN =
for (i in Difference) {
ifelse(i>referenceValue,"HIGH","LOW")
}
)
output
}
I also tried...
if (i>referenceValue) {
apply(output,1,print("HIGH"))
}else(print("LOW")) {}
}
)
output
}
Regardless, both end up giving me the error message,
c("'for (i in Difference) {' is not a function, character or symbol", "' ifelse(i > referenceValue, \"HIGH\", \"LOW\")' is not a function, character or symbol", "'}' is not a function, character or symbol")
The expected output should look like:
Patient Difference Toxicity
3 21.430000 LOW
5 46.430000 HIGH
6 3.570000 LOW
7 57.140000 HIGH
8 42.310000 HIGH
10 28.570000 HIGH
11 0.000000 LOW
12 16.070000 LOW
13 51.790000 HIGH
14 35.710000 HIGH
Is there a better way for me to organize the last loop?

Answer 1

Since you seem to be using tibbles anyway, here's a much shorter version using dplyr and tidyr:
> d %>%
gather(key = tscore,value = score,T1Score:T4Score) %>%
group_by(Patient) %>%
summarise(Difference = max(score,na.rm = TRUE) - min(score,na.rm = TRUE)) %>%
ungroup() %>%
mutate(AvgDifference = mean(Difference),
Toxicity = if_else(Difference > mean(Difference),"HIGH","LOW"))
# A tibble: 10 x 4
Patient Difference AvgDifference Toxicity
<int> <dbl> <dbl> <chr>
1 3 21.4 30.3 LOW
2 5 46.4 30.3 HIGH
3 6 3.6 30.3 LOW
4 7 57.1 30.3 HIGH
5 8 42.3 30.3 HIGH
6 10 28.6 30.3 LOW
7 11 0 30.3 LOW
8 12 16.1 30.3 LOW
9 13 51.8 30.3 HIGH
10 14 35.7 30.3 HIGH
I think maybe your expected output might have been based on a slightly different average difference, so this output is very slightly different.
And a much simpler base R version if you prefer:
d$min <- apply(d[,2:5],1,min,na.rm = TRUE)
d$max <- apply(d[,2:5],1,max,na.rm = TRUE)
d$diff <- d$max - d$min
d$avg_diff <- mean(d$diff)
d$toxicity <- with(d,ifelse(diff > avg_diff,"HIGH","LOW"))
A few notes on your existing code:
as.data.frame((cbind(minValue,maxValue))) is not an advisable way to create data frames. This is more awkward than simply doing data.frame(minValue = minValue,maxValue = maxValue) and risks unintended coercion from cbind.
ave is for computing summaries over groups; just use mean if you have a single vector
The FUN argument in apply expects a function, not an arbitrary expression, which is what you're trying to pass at the end. The general syntax for an "anonymous" function in that context would be apply(...,FUN = function(arg) { do some stuff and return exactly the thing you want}).