Question: how can I compare two groups from each other in R
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3.8 years ago by
Learner 240
Learner 240 wrote:

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

R • 928 views
ADD COMMENTlink written 3.8 years ago by Learner 240

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

ADD REPLYlink written 3.8 years ago by VHahaut1.1k

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

ADD REPLYlink written 3.8 years ago by Learner 240

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

ADD REPLYlink written 3.8 years ago by Lluís R.1000
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