Logistic Regression with 200K features in R?

Dear List,

I'm quite new to R and want to do logistic regression with a 200K
feature data set (around 150 training examples).

I'm aware that I should use Naive Bayes but I have a more general
question about the capability of R handling very high dimensional data.

Please consider the following R code where "mygenestrain.tab" is a 150
by 200000 matrix:

traindata <- read.table('mygenestrain.tab');
mylogit <- glm(V1 ~ ., data = traindata, family = "binomial");

When executing this code I get the following error:

Error in terms.formula(formula, data = data) :
  allocMatrix: too many elements specified
Calls: glm ... model.frame -> model.frame.default -> terms -> terms.formula
Execution halted

Is this because R can't handle 200K features or am I doing something
completely wrong here?

Thanks a lot for your help!

best Regards,

Romeo