I am tying to replace 0's in my dataframe of thousands of rows and columns with half the minimum value greater than zero from that column. I would also not want to include the first four columns as they are indexes.
So if I start with something like this:
index <- c("100p", "200p", 300p" 400p")
ratio <- c(5, 4, 3, 2)
gene <- c("gapdh", NA, NA,"actb"
species <- c("mouse", NA, NA, "rat")
a1 <- c(0,3,5,2)
b1 <- c(0, 0, 4, 6)
c1 <- c(1, 2, 3, 4)
as.data.frame(q) <- cbind(index, ratio, gene, species, a1, b1, c1)
index ratio gene species a1 b1 c1
100p 5 gapdh mouse 0 0 1
200p 4 NA NA 3 0 2
300p 3 NA NA 5 4 3
400p 2 actb rat 2 6 4
I would hope to gain a result such as this:
index ratio gene species a1 b1 c1
100p 5 gapdh mouse 1 2 1
200p 4 NA NA 3 2 2
300p 3 NA NA 5 4 3
400p 2 actb rat 2 6 4
I have tried the following code:
apply(q[-4], 2, function(x) "[<-"(x, x==0, min(x[x > 0]) / 2))
but I keep getting the error:Error in min(x[x > 0])/2 : non-numeric argument to binary operator
Any help on this? Thank you very much!
We can use lapply and replace the 0 values with minimum value in column by 2.
cols<- 5:7
q[cols] <- lapply(q[cols], function(x) replace(x, x == 0, min(x[x>0], na.rm = TRUE)/2))
q
# index ratio gene species a1 b1 c1
#1 100p 5 gapdh mouse 1 2 1
#2 200p 4 <NA> <NA> 3 2 2
#3 300p 3 <NA> <NA> 5 4 3
#4 400p 2 actb rat 2 6 4
In dplyr, we can use mutate_at
library(dplyr)
q %>% mutate_at(cols,~replace(., . == 0, min(.[.>0], na.rm = TRUE)/2))
data
q <- structure(list(index = structure(1:4, .Label = c("100p", "200p",
"300p", "400p"), class = "factor"), ratio = c(5, 4, 3, 2), gene = structure(c(2L,
NA, NA, 1L), .Label = c("actb", "gapdh"), class = "factor"),
species = structure(c(1L, NA, NA, 2L), .Label = c("mouse",
"rat"), class = "factor"), a1 = c(0, 3, 5, 2), b1 = c(0,
0, 4, 6), c1 = c(1, 2, 3, 4)), class = "data.frame", row.names = c(NA, -4L))