[R] Linear models interaction

[gauravbhatti]

My data looks like following:
                    cera3[i, ] batch lcl29 pdt
Untreated     3.185867     1     0   0
Untreated.4   3.185867     0     0   0
LCL29          4.357552     1     1   0
LCL29.6       3.446256     0     1   0
PDT           2.765535     1     0   1
PDT.5         3.584963     0     0   1
PDT+LCL29.1   2.867896     1     1   1
PDT+LCL29.3   2.827819     0     1   1

As you can see there are three factorls batch , lcl29 and pdt. I am trying
to fit the model: 
Y = batch +pdt*lcl29. I get the following coefficients:
                    Estimate Std. Error    t value     Pr(>|t|)
(Intercept)  3.1524122  0.2487796 12.6715049 1.242191e-12
batch1      -0.2267947  0.2291590 -0.9896827 3.314508e-01
lcl291       0.6350186  0.3122910  2.0334194 5.233525e-02
pdt1         0.1046388  0.3122910  0.3350684 7.402619e-01
lcl291:pdt1 -0.6633316  0.4521381 -1.4670995 1.543419e-01

I know that the coef. of lcl291 i.e 0.635 is difference in means between
rows with lcl29 present alone and untreated ones. Same is true for the coef
of PDT1. However I am not sure about the coefficient of  lcl291:pdt1. 
where does this value come from? How is it calculated?
what does it tell? Is it Interaction versus all the rest because it is
certailnly not interaction versus untreated? 

Thank You

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