Removing Columns Named "NA"

Question

I'm dealing with some RNA-seq count data for which I have ~60,000 columns containing gene names and 24 rows containing sample names. When I did some gene name conversions I was left with a bunch of columns that are named NA. I know that R handles NA differently than a typical column name and my question is how do I remove these columns. Here is an example of my data.

  "Gene1"  "Gene2"  "Gene3"  NA  "Gene4"
1  10       11       12      10   15
2  13       12       50      40   30
3  34       23       23      21   22

I would like it to end up like

  "Gene1"  "Gene2"  "Gene3"  "Gene4"
1  10       11       12       15
2  13       12       50       30
3  34       23       23       22

I did identify some R code that worked for others but not for me

df<-df[, grep("^(NA)", names(df), value = TRUE, invert = TRUE)]

Answer 1

Looks like you have an actual NA in your names, instead of "NA". The former represents a missing value, the latter is a character string that looks like the symbol that represents the missing value. Use:

df <- df[!is.na(names(df))]

Illustrating with iris:

> head(iris)
  Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1          5.1         3.5          1.4         0.2  setosa
2          4.9         3.0          1.4         0.2  setosa
3          4.7         3.2          1.3         0.2  setosa
4          4.6         3.1          1.5         0.2  setosa
5          5.0         3.6          1.4         0.2  setosa
6          5.4         3.9          1.7         0.4  setosa
> names(iris)[2:3] <- NA
> head(iris)
  Sepal.Length  NA  NA Petal.Width Species
1          5.1 3.5 1.4         0.2  setosa
2          4.9 3.0 1.4         0.2  setosa
3          4.7 3.2 1.3         0.2  setosa
4          4.6 3.1 1.5         0.2  setosa
5          5.0 3.6 1.4         0.2  setosa
6          5.4 3.9 1.7         0.4  setosa
> head(iris[!is.na(names(iris))])
  Sepal.Length Petal.Width Species
1          5.1         0.2  setosa
2          4.9         0.2  setosa
3          4.7         0.2  setosa
4          4.6         0.2  setosa
5          5.0         0.2  setosa
6          5.4         0.4  setosa