Dear list,

I am a fairly new user of R and I am currently trying to use the HTqPCR package to analyze qPCR data derived from the Biomark platform (96.96). For each chip I have 9216 Ct values, of which I wanted to eliminate those below or above a certain threshold. I tried to use the setCategory and filterCategory function for this purpose but ran into problems (I did not get any warning messages).

**Loading data**
>raw_a1p1_v <- readCtData(files = "AssayRound1_Plate1_lin_deriv_auto_global.csv", path = expath, format = "BioMark", n.features = 96 * 96, n.data = 1)

**Set category for Ct values of a certain threshold**
>setCategory(raw_a1p1_v, Ct.max = 26, Ct.min = 10, flag = FALSE, quantile = NULL)
Categories after Ct.max and Ct.min filtering:
             AssayRound1_Plate1_lin_deriv_auto_global
OK                                               7726
Undetermined                                      992
Unreliable                                        498
> x <- setCategory(raw_a1p1_v, Ct.max = 26, Ct.min = 10, flag = FALSE, quantile = NULL)
Categories after Ct.max and Ct.min filtering:
             AssayRound1_Plate1_lin_deriv_auto_global
OK                                               7726
Undetermined                                      992
Unreliable                                        498

**Filter category**
> z <- filterCategory(x, na.categories = c("Undetermined", "Unreliable"))
> summary(z)
 AssayRound1_Plate1_lin_deriv_auto_global
 Min.   :10.31                           
 1st Qu.:12.62                           
 Median :14.54                           
 Mean   :15.65                           
 3rd Qu.:18.34                           
 Max.   :23.86                           
 NA's   :1728

As you can see, the number of NAs after filtering is not the sum of "Undetermined"/"Unreliable" after setCategory. Why is that? I expected to have 1490 NAs for z after filtering. I would appreciate any help or suggestions to help me understand this discrepancy.

Thanks a lot,

Saskia

*Here is the session info:*

R version 3.6.0 (2019-04-26)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 17134)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

attached base packages:
[1] parallel  stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] raster_3.0-7        sp_1.3-2            lattice_0.20-38     plyr_1.8.5          gtools_3.8.1       
 [6] gplots_3.0.1.1      ggplot2_3.2.1       HTqPCR_1.40.0       limma_3.42.0        RColorBrewer_1.1-2 
[11] Biobase_2.46.0      BiocGenerics_0.32.0

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.3            rstudioapi_0.10       zlibbioc_1.32.0       munsell_0.5.0        
 [5] colorspace_1.4-1      R6_2.4.1              rlang_0.4.2           caTools_1.17.1.2     
 [9] tools_3.6.0           grid_3.6.0            gtable_0.3.0          KernSmooth_2.23-15   
[13] affy_1.64.0           withr_2.1.2           lazyeval_0.2.2        tibble_2.1.3         
[17] preprocessCore_1.48.0 lifecycle_0.1.0       crayon_1.3.4          affyio_1.56.0        
[21] BiocManager_1.30.10   codetools_0.2-16      bitops_1.0-6          gdata_2.18.0         
[25] pillar_1.4.2          compiler_3.6.0        scales_1.1.0          stats4_3.6.0         
[29] pkgconfig_2.0.3