Hello,

I am trying to generate a qDE.limma file for subsequent analysis and visual representation. Strangely, I lose my gene names after running the limmaCtData function. Am I doing something wrong?

raw <- readCtData(files = "1131361180.csv", path = path, format = "BioMark", n.features =48, n.data = 48)

raw.D1filt <- raw[, c(1,2,4,5,7,10,13,16,17,20,23,25,26,28,31,34,37,40)]

summary(FData)
       X           featureNames featureType   featurePos  featureClass
 Min.   : 1.00   ACTB    : 2    Target:48   S48-A01: 1   RF     :12   
 1st Qu.:12.75   APOBEC3G: 2                S48-A02: 1   TH1    : 8   
 Median :24.50   ASC4   : 2                S48-A03: 1   TH2    : 8   
 Mean   :24.50   BATF    : 2                S48-A04: 1   Tfh    : 4   
 3rd Qu.:36.25   BCL6    : 2                S48-A05: 1   Norm   : 2   
 Max.   :48.00   CD274   : 2                S48-A06: 1   PDL1   : 2   
                 (Other) :36                (Other):42   (Other):12 

fData(raw.D1filt) <- FData

> show(raw.D1filt)
An object of class "qPCRset"
Size:  48 features, 18 samples
Feature types:          
Feature names:         PD1 BCL6 BATF ...
Feature classes:          
Feature categories:     OK 
Sample names:             1P3SB 1CPASB 1P3SB ...

covariatesm3<- pData(raw.D1filt)

designm3 <- (model.matrix(~0 +DAdj:Ant, covariatesm3))[, -c(1, 5, 6)]
> colnames(designm3) <- PDataColnamesm3

show(designm3)
   D1MPNS D1NNS D1P3NS D1CPASB D1MPSB D1NSB D1P3SB D1PICSB D1R8SB
1       0     0      0       0      0     0      1       0      0
2       0     0      0       1      0     0      0       0      0
3       0     0      0       0      0     0      1       0      0
4       0     0      0       1      0     0      0       0      0
5       0     0      1       0      0     0      0       0      0
6       0     0      1       0      0     0      0       0      0
7       0     0      0       0      0     0      0       1      0
8       0     0      0       0      0     0      0       1      0
9       0     0      0       0      0     1      0       0      0
10      0     0      0       0      0     1      0       0      0
11      0     1      0       0      0     0      0       0      0
12      0     0      0       0      1     0      0       0      0
13      0     1      0       0      0     0      0       0      0
14      0     0      0       0      1     0      0       0      0
15      1     0      0       0      0     0      0       0      0
16      1     0      0       0      0     0      0       0      0
17      0     0      0       0      0     0      0       0      1
18      0     0      0       0      0     0      0       0      1

contrastsm3 <- makeContrasts(D1MPNS-D1NNS, D1P3NS-D1NNS, D1CPASB-D1NSB, D1MPSB-D1NSB, D1P3SB-D1NSB, D1PICSB-D1NSB, D1R8SB-D1NSB, levels= designm3)

qDE.limmam3 <- limmaCtData(raw.D1filt, design = designm3, contrasts = contrastsm3, sort = TRUE, stringent = TRUE, ndups = 1, spacing = 1)

featureNames(qDE.limmam3)
 [1] "4"  "10" "14" "7"  "17" "35" "3"  "25" "28" "40" "37" "38" "6"  "2"  "5" 
[16] "18" "26" "15" "22" "36" "12" "9"  "32" "29" "41" "33" "46" "16" "31" "39"
[31] "1"  "11" "24" "43" "34" "30" "45" "8"  "13" "19" "20" "21" "23" "27" "42"
[46] "44" "47" "48"

My subesequent graphs only have these number values for the gene names. Am I doing something wrong? I know that I can change the feature names in themselves but this does not change the actual names of the samples when they are graphed via heatmapSig or similar operations. Thanks for your help!

Okay, so I have solved my own issue. Given that I have duplicate names in my featureNames, the limmaCTData function will replace these names with numbers to properly sort out the data. So, if the featureNames are changed to unique names, then the names are conserved afterward. This seems obvious to me now in afterthought. :)