[BioC] cellHTS Repeat Values in Text Output

[Mark Dane]

Hi,

I am seeing a problem with the text output in my multi-channel experiment. I have different types of data so I want to normalize and score the channels separately. Therefore, I do not want to run summarizeReplicates. I think the following will show what I am doing:

x <- readPlateList("Platelist.txt", name=experimentName, path=dataPath)
x <- configure(x, "Description.txt", "Plateconf.txt", "Screenlog.txt",
               path=dataPath) 
xn <- normalizePlates(x, scale="multiplicative", method="median", 
                      varianceAdjust="none")
xsc <- scoreReplicates(xn, sign="-", method="zscore") 
xsc at state[3]=TRUE
getTopTable(cellHTSlist=list("raw"=x,"normalized"=xn, "scored"=xsc),
            file="testtable.txt")

The output in testtable.txt (and similarly in writeReport's text output) has repeated values that are not what is actually in the cellHTS objects.

raw'G01plate	position	well	score	wellAnno	finalWellAnno	raw_r1_ch1	raw_r2_ch1	raw_r1_ch2	raw_r2_ch2	median_ch1	diff_ch1	median_ch2	diff_ch2	raw/PlateMedian_r1_ch1	raw/PlateMedian_r2_ch1	raw/PlateMedian_r1_ch2	raw/PlateMedian_r2_ch2	normalized_r1_ch1	normalized_r2_ch1	normalized_r1_ch2	normalized_r2_ch2
3	145	G01	3.33	sample	sample	80	80	80	80	80	0	80	0	0.0502	0.0502	0.0502	0.0502	0.05	0.05	0.05	0.05
1	7	A07	3.33	sample	sample	80	80	80	80	80	0	80	0	0.051	0.051	0.051	0.051	0.051	0.051	0.051	0.051
3	202	I10	3.27	sample	sample	110	110	110	110	110	0	110	0	0.069	0.069	0.069	0.069	0.069	0.069	0.069	0.069

Is it ok to force the scored state of xsc to TRUE? Please let me know if I'm using this correctly. I really appreciate your prior quick and helpful responses.

thank you,

Mark Dane
Computational Biology Master Student
Oregon Health and Science University



> sessionInfo()
R version 3.0.0 (2013-04-03)
Platform: x86_64-apple-darwin10.8.0 (64-bit)

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

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

other attached packages:
 [1] lattice_0.20-15    gdata_2.12.0.2     cellHTS2_2.25.1    locfit_1.5-9.1    
 [5] hwriter_1.3        vsn_3.29.0         splots_1.27.0      genefilter_1.43.0 
 [9] Biobase_2.21.2     BiocGenerics_0.7.2 RColorBrewer_1.0-5 spade_1.9.0       
[13] igraph0_0.5.7     

loaded via a namespace (and not attached):
 [1] affy_1.39.2           affyio_1.29.0         annotate_1.39.0      
 [4] AnnotationDbi_1.23.11 BiocInstaller_1.11.1  Category_2.27.1      
 [7] DBI_0.2-7             feature_1.2.8         flowCore_1.27.15     
[10] graph_1.39.0          GSEABase_1.23.0       gtools_2.7.1         
[13] IRanges_1.19.8        ks_1.8.12             limma_3.17.12        
[16] MASS_7.3-26           prada_1.37.0          preprocessCore_1.23.0
[19] RBGL_1.37.2           robustbase_0.9-7      rrcov_1.3-3          
[22] RSQLite_0.11.3        splines_3.0.0         stats4_3.0.0         
[25] survival_2.37-4       tools_3.0.0           XML_3.95-0.2         
[28] xtable_1.7-1          zlibbioc_1.7.0