[R] Newbie: Translating GLM SAS code into R

[Peyuco Porras Porras .]

Dear all;

I'm looking for some help in translating the following SAS code to R. The code represents a 

factorial design plus 1 control plot (2 x 2 + 1). The data is the following
	
BLOCK	FA	FB	FC	Y
1	0	0	0	15.33
1	1	0	0	14.40
1	1	1	0	15.49
1	1	0	1	16.87
1	1	1	1	18.84
2	0	0	0	15.97
2	1	0	0	16.18
2	1	1	0	14.52
2	1	0	1	18.04
2	1	1	1	19.81
3	0	0	0	15.60
3	1	0	0	14.79
3	1	1	0	14.30
3	1	0	1	17.18
3	1	1	1	18.37
4	0	0	0	15.22
4	1	0	0	16.24
4	1	1	0	15.97
4	1	0	1	16.51
4	1	1	1	19.05

The SAS code is:

proc glm data=test;
class BLOCK FA FB FC;
model Y = BLOCK FA FB(FA) FC(FA) FB*FC(FA)/alpha=0.05;
random BLOCK/test;
lsmeans FB*FC(FA)/pdiff stderr;
quit; run;

I've tried:

library(nlme)
options(contrasts=c("contr.SAS","contr.SAS"))

data.gr<-groupedData(Y~1|BLocK,data=data)

data.gr$BLocK<-as.factor(data.gr$BLocK);data.gr$FA<-as.factor(data.gr$FA)
data.gr$FB<-as.factor(data.gr$FB);data.gr$FC<-as.factor(data.gr$FC)

mod1<-lme(Y~FA+(FB*FC)/FA,random=~1|BLOCK,data=data.gr)

but I can't get the model works and I can't figure out how can I do it.

I'll appreciate any ideas

Best regards
P. Porras