Identify the differentially expressed genes

A slight difference of parameter will make a totally different gene list.. Must watch out what we did.. As I knew currently, the most important things are the design matrix and the "coefficient". There is other minor adjustment such as topTable(adjust), which is for p-value adjustment, but I would like to stick to "FDR" first.

>design<-cbind(Dye=1, Beta7=c(1,-1,-1,1,1,-1))
>fit<-lmFit(nordata,design,weights=NULL)
>fit<-eBayes(fit)
>Table1<-topTable(fit,coef="Dye",adjust="fdr")
>Table1$Name<-substring(Table1$Name,1,12)
>Table1
             ID         Name    logFC   AveExpr        t      P.Value  adj.P.Val        B
10747 H200005892 HLA-DQB1 - M 1.566674 12.002316 13.24244 9.728991e-06 0.02544872 3.807952
8819  H200006035 TYRP1 - Tyro 1.661024 12.159866 13.00588 1.082891e-05 0.02544872 3.733779
15579 H200006025 DAP - Death- 1.435546 12.644359 12.47848 1.384254e-05 0.02544872 3.559907
9305  H200005780 C19orf7 - Ch 1.353122 13.101057 12.39516 1.440280e-05 0.02544872 3.531313
12312 H200011083 KIAA0692 - K 1.358942 10.883141 12.14326 1.626307e-05 0.02544872 3.442918
10913 H200013564 RBMX - RNA b 1.289367 12.517112 11.79361 1.932612e-05 0.02544872 3.315169
15126 H200007318 HAP1 - Hunti 1.623051 11.536758 11.66654 2.060115e-05 0.02544872 3.267230
17192 H200013376 SLC8A2 - Sol 1.737073  4.501546 11.66589 2.060792e-05 0.02544872 3.266983
16546 H200006019 PPP5C - Prot 1.489265 10.131609 11.66234 2.064493e-05 0.02544872 3.265631
20416 H200006376 ARHA - Ras h 1.884627 13.675812 11.62780 2.100903e-05 0.02544872 3.252450

>design<-c(1,-1,-1,1,1,-1)
>fit<-lmFit(nordata,design,weights=NULL)
>fit<-eBayes(fit)
>Table2<-topTable(fit,adjust="fdr")
>Table2$Name<-substring(Table2$Name,1,12)
>Table2

          ID         Name      logFC   AveExpr          t      P.Value adj.P.Val            B
6647  H200017286 GPR2 - G pro -2.4511865  7.787727 -10.770494 8.123551e-06 0.1834054  1.171025368
11025 H200018884 Homo sapiens -1.5975971  6.616640  -8.764280 3.424187e-05 0.2828096  0.707261894
3152  H200012024 ITGA1 - Inte  1.2673703  6.979029   8.390349 4.617165e-05 0.2828096  0.594759959
21405 H200007427 CENTG2 - Cen -1.1868237  6.092311  -8.290405 5.010579e-05 0.2828096  0.562965478
4910  H200003784 SEMA5A - Sem -1.3489761  6.809355  -6.893363 1.723876e-04 0.6096875  0.027552798
7832  H200004937 Homo sapiens -1.2424628  6.301858  -6.851093 1.794831e-04 0.6096875  0.008303493
18925 H200003977 F5 - Coagula -1.1046977  7.498769  -6.547843 2.410666e-04 0.6096875 -0.135922701
20812 H200001929 EPLIN - Epit -1.0963658  8.615247  -6.294852 3.107515e-04 0.6096875 -0.264929553
16442 H200001079 EGFL5 - EGF- -0.9630056  7.739278  -6.273861 3.174729e-04 0.6096875 -0.276006763
1755  H200014446 P2Y5 - Purin -0.9152066 12.226345  -6.147830 3.613902e-04 0.6096875 -0.343757901