How to remove rows with NAs only if they are present in more than certain percentage of columns?

Question

I want to use na.omit (data) for the following example dataset, but on a condition so as to remove rows with NAs only when they are present in lets say "more than 30%" of the columns.

data:

        C1     C2     C3     C4     C5
Gene1   0.07   NA     0.05   0.07   0.07
Gene2   0.2    0.18   0.16   0.15   0.15
Gene3   NA     0.93   0.9    NA     0.92
Gene4   0.32   0.05   0.12   0.13   0.05
Gene5   0.44   0.53   0.46   0.03   0.47
Gene6   NA     0.34   NA     0.8    NA
Gene7   0.49   0.55   0.67   0.49   0.89
Gene8   0.25   NA     0.49   NA     NA
Gene9   0.1    0.1    0.05   NA     0.09

So the resulting file should be as follows:

        C1     C2     C3     C4     C5
Gene1   0.07   NA     0.05   0.07   0.07
Gene2   0.2    0.18   0.16   0.15   0.15
Gene4   0.32   0.05   0.12   0.13   0.05
Gene5   0.44   0.53   0.46   0.03   0.47
Gene7   0.49   0.55   0.67   0.49   0.89
Gene9   0.1    0.1    0.05   NA     0.09

Thanks for the help!

Answer 1

You can subset based on the row sums of NA values:

test[!rowSums(is.na(test)) > ncol(test)*.3,]

        C1   C2   C3   C4   C5
Gene1 0.07   NA 0.05 0.07 0.07
Gene2 0.20 0.18 0.16 0.15 0.15
Gene4 0.32 0.05 0.12 0.13 0.05
Gene5 0.44 0.53 0.46 0.03 0.47
Gene7 0.49 0.55 0.67 0.49 0.89
Gene9 0.10 0.10 0.05   NA 0.09

Answer 2

Here is another version with Reduce

df1[!Reduce(`+`, lapply(df1, is.na)) > ncol(df1)*0.3,]
#       C1   C2   C3   C4   C5
#Gene1 0.07   NA 0.05 0.07 0.07
#Gene2 0.20 0.18 0.16 0.15 0.15
#Gene4 0.32 0.05 0.12 0.13 0.05
#Gene5 0.44 0.53 0.46 0.03 0.47
#Gene7 0.49 0.55 0.67 0.49 0.89
#Gene9 0.10 0.10 0.05   NA 0.09