That won't always work. The data needs to be numeric and data.matrix is not strict enough to satisfy that. In all probability, your datExpr is a data.frame that has factors or logical columns which data.matrix converts to numeric type, but does not really have a non-convertible column. zx8754's answer that points OP to ensure all data is numeric is the right way to go.

See sample code that shows why data.matrix won't work:

x <- c("A","B","C")
x_fac <- factor(x, levels = c("B","A","C"), ordered = TRUE)

################

df_fac <- data.frame(col1=c(1,2,3), col2=x_fac, col3=c(TRUE,FALSE,TRUE), stringsAsFactors = FALSE) #col2 is a factor here
df_fac

  col1 col2  col3
1    1    A  TRUE
2    2    B FALSE
3    3    C  TRUE

data.matrix(df_fac)

     col1 col2 col3
[1,]    1   NA    1
[2,]    2   NA    0
[3,]    3   NA    1
Warning message:
In data.matrix(data.frame(col1 = c(1, 2, 3), col2 = x, col3 = c(TRUE,  :
  NAs introduced by coercion

################

df_nonfac <- data.frame(col1 = c(1,2,3), col2 = x, col3 = c(TRUE,FALSE,TRUE), stringsAsFactors = FALSE) #col2 is not a factor here
  col1 col2  col3
1    1    A  TRUE
2    2    B FALSE
3    3    C  TRUE

data.matrix(df_nonfac)
     col1 col2 col3
[1,]    1    2    1
[2,]    2    1    0
[3,]    3    3    1

See how it works perfectly when columns are numeric, logical or factor but not otherwise? The trick is to handle non-numeric columns, not use a data.matrix blindly.