[R] how to parse out fitting statistics and write them into a data frame?

[weix1]

hello, everyone: 
I am conducting t test between drug and control for about 50,000 gene using
the following syntax (treatment is factor): 

result<- lapply(split(data, data$gene),function(x) lm(value~treatment,x) 
  
however, the result is a list and i do not know whether more model fitting
statistics (like p value of t test) is included in "result" or not. If i
print the first element of resut i got the followings: 

> result[1] 
$`1007_s_at` 

Call: 
lm(formula = logvalue ~ treatment, data = x) 

Coefficients: 
 (Intercept)  treatmentveh   
      8.9403        0.3232   

> summary(result[1]) 
          Length Class Mode 
1007_s_at 13     lm    list 
> 

So my question is whether more fitting statistics (other than coefficient
estimation, like p value) are included in the "result". If yes, how can I
parse them into a data frame so that i can output those statistics into a
.csv file that can be shared with my clients. If not, how can I modify the
code so that more stat can be computed and stored? 
any constructive suggestions are welcome. 

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