[BioC] differntially expressed gene

[Prasad Siddavatam]

Hi,

I sincerely thank Dr.Brown for his response to my earlier post on design matrix.

I have two questions....1. about the discrepancies in my DE results 
                        2. B-values 
These are my target files
FileName	Cy3	Cy5	Original Names	
HIDEN_1.gpr	Ref	HI_Inf	Heat_Inactivated_1	
HIDEN_2.gpr	Ref	HI_Inf	Heat_Inactivated_2	
HIDEN_3.gpr	Ref	HI_Inf	Heat_Inactivated_3	
infected_1.gpr	Ref	Infect	Live_Infection_1	
infected_2.gpr	Ref	Infect	Live_Infection_2	
infected_3.gpr	Ref	Infect	Live_Infection_3

design:
    HI_Inf Infect
      1      0
      1      0
      1      0
      0      1
      0      1
      0      1 
contrast:
        Contrasts
Levels   HI_INF INF INFvsHI_INF
  HI_Inf      1   0          -1
  Infect      0   1           1
When I used the above matrix and contrasts, I found 270 and 2484 DE genes (for 
HI_INF and INF, respectively). 

But when I divided the data into two separate analyses 
1. For HI_INF I found 608 DE genes 
HIDEN_1.gpr	Ref	HI_Inf	Heat_Inactivated_1	
HIDEN_2.gpr	Ref	HI_Inf	Heat_Inactivated_2	
HIDEN_3.gpr	Ref	HI_Inf	Heat_Inactivated_3
2. For INF I found 868 DE genes 
infected_1.gpr	Ref	Infect	Live_Infection_1	
infected_2.gpr	Ref	Infect	Live_Infection_2	
infected_3.gpr	Ref	Infect	Live_Infection_3

Why is this difference? technically those should be same because rest of the 
steps were similar between the two.
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I also found that there are some genes with negative "B Values" but < 0.5 
adjusted p.values and p.values...see below
   logFC         t     P.Value     adj.P.Val    B
 -0.6740520 -3.655211 0.006576695 0.04978582 -2.453619
 -0.3866386 -3.655013 0.006578564 0.04978582 -2.453912
 -0.6554844 -3.652845 0.006599049 0.04992410 -2.457116

In this case, can I delete the genes with negative B-values though adjusted 
p.values and p.values are < 0.05?

Your suggestions are highly appreciated
-regards
Prasad