how can I compare two groups from each other in R

Question

[Learner]

I have a Control group with two replicate and two treated group with two replicate. I want to know how I can identify the sample that are significantly different between control and treated 1 (higher expression) while significant different between control and treated 2 (lower expression)

This is an example data

df<-structure(list(C1 = c(0.003926348, 0.001642442, 6.72e-05, 0.000314789, 
0.00031372, 0.000196342, 0.01318432, 8.86e-05, 0.005671017, 0.003616196, 
0.026635645, 0.001136402, 0.000161111, 0.005777738, 0.000145104, 
0.000996546, 4.27e-05, 0.000114159, 0.001152384, 0.002860251, 
0.000284873), C2 = c(0.003901373, 0.001526195, 6.3e-05, 0.000387266, 
0.000312458, 0.000256647, 0.012489205, 0.00013071, 0.005196136, 
0.003059834, 0.024624562, 0.001025486, 0.000144964, 0.005659078, 
0.000105755, 0.000844871, 5.88e-05, 0.000118831, 0.000999354, 
0.002153167, 0.000214486), T1 = c(0.003646894, 0.001484503, 4.93e-05, 
0.00036715, 0.000333378, 0.000244199, 0.010286787, 6.48e-05, 
0.006180042, 0.00387491, 0.025428464, 0.001075376, 0.000122088, 
0.005448152, 0.000103301, 0.000974826, 4.32e-05, 0.000109876, 
0.001030364, 0.002777244, 0.000221169), T2 = c(0.00050388, 0.001135969, 
0.000113829, 2.14e-06, 0.00010293, 0.000315704, 0.01160593, 8.46e-05, 
0.004495437, 0.003062559, 0.018662663, 0.002096675, 0.000214814, 
0.002177849, 8.61e-05, 0.001057254, 3.27e-05, 0.000115822, 0.008133257, 
0.021657018, 0.000261339), G1 = c(0.001496712, 0.001640965, 0.000129124, 
3.02e-06, 0.000122839, 0.000305686, 0.01378774, 0.000199637, 
0.00534668, 0.00300097, 0.023290941, 0.002595433, 0.000262479, 
0.002926346, 0.000125655, 0.001302624, 4.89e-05, 0.000122862, 
0.009851791, 0.017621282, 0.000197561), G2 = c(0.00114337, 0.001285636, 
0.000122848, 2.46e-06, 9.1e-05, 0.000288897, 0.012288087, 0.000122286, 
0.002575368, 0.002158011, 0.022008677, 0.002017026, 0.000241754, 
0.003340175, 0.00013424, 0.001517655, 4.78e-05, 0.000110353, 
0.008293286, 0.018999466, 0.000191129)), .Names = c("C1", "C2", 
"T1", "T2", "G1", "G2"), row.names = c("A", "B", "C", "D", "E", 
"F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "PP", 
"TT", "EE", "FF", "AS"), class = "data.frame")

The first two columns are the control the second two columns are the treated 1 the third two columns are the treated 2

[VHahaut]

Could you tell us more about the type of data you have?

[Learner]

@Radek data are continues values and not count values (basically they are Mass spec data) . is it enough?

[Lluís R.]

I think that in Bioconductor you have a workflow about how to analyze Mass spec data. But I am unsure