Dear all, I’m trying to analyse 7 plates in a siRNA experiment.
These plates have 48 wells but only 24 are used. Wells on the edges are empty (all wells from A01 to A08, F01 to F08 and X01 and X08. Where X goes from A to F).
I’m trying to analyse this using cellHTS2 from Huber’s lab.
First I tried to explain the wells in the PlateConf.txt file
Wells: 48
Plates: 7
Plate Well Content
* * sample
* A0[1-8] empty
* F0[1-8] empty
* B01 empty
* B08 empty
* C01 empty
* C08 empty
* D01 empty
* D08 empty
* E01 empty
* E08 empty
This give a Error in well[[i]] : subscript out of bounds
Only wells from A are valid :
Wells: 48
Plates: 7
Plate Well Content
* * sample
* A0[1-8] empty
So I tried then to include this empty wells in the Screenlog.txt, e.g. (for 2 plates):
Plate Sample Well Flag Comment
1 1 A01 NA Empty
2 1 A01 NA Empty
1 1 A02 NA Empty
2 1 A02 NA Empty
1 1 A03 NA Empty
2 1 A03 NA Empty
1 1 A04 NA Empty
2 1 A04 NA Empty
1 1 A05 NA Empty
2 1 A05 NA Empty
1 1 A06 NA Empty
2 1 A06 NA Empty
1 1 A07 NA Empty
2 1 A07 NA Empty
1 1 A08 NA Empty
……...
In this case I obtain : Error in convertWellCoordinates(slog$Well, pdim(object)) :
Invalid position IDs in 'x’.
And again if I use only A wells, it works. So my question is … How do I have to specify this empty wells to avoid errors in normalisation and other subsequent analysis ?
my sessionInfo is :
> sessionInfo()
R version 3.2.2 (2015-08-14)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: OS X 10.11.3 (El Capitan)
locale:
[1] C
attached base packages:
[1] grid parallel stats graphics grDevices utils datasets methods base
other attached packages:
[1] cellHTS2_2.32.0 locfit_1.5-9.1 hwriter_1.3.2 vsn_3.36.0 splots_1.34.0 genefilter_1.50.0 Biobase_2.28.0 BiocGenerics_0.14.0 RColorBrewer_1.1-2
loaded via a namespace (and not attached):
[1] pcaPP_1.9-60 prada_1.44.0 BiocInstaller_1.18.5 DEoptimR_1.0-4 GenomeInfoDb_1.4.3 tools_3.2.2 zlibbioc_1.14.0 annotate_1.46.1 RSQLite_1.0.0
[10] preprocessCore_1.30.0 lattice_0.20-33 Matrix_1.2-3 graph_1.46.0 DBI_0.3.1 Category_2.34.2 mvtnorm_1.0-5 cluster_2.0.3 S4Vectors_0.6.6
[19] IRanges_2.2.9 stats4_3.2.2 robustbase_0.92-5 GSEABase_1.30.2 rrcov_1.3-11 AnnotationDbi_1.30.1 RBGL_1.44.0 XML_3.98-1.4 survival_2.38-3
[28] limma_3.24.15 splines_3.2.2 MASS_7.3-45 xtable_1.8-2 affy_1.46.1 affyio_1.36.0 That’s all
Thank you very much in advance