[BioC] problems normalizing in limma

Anand C.Patel acpatel at usa.net
Thu Oct 13 02:35:32 CEST 2005


I'm having troubles with some new arrays we're working with.

After some effort, I've managed to read .csv output from PerkinElmer ScanArray
into an RGList object.

Warning to anyone else -- the .gpr files this program generates do not conform
strictly to the gpr file format, and will make both limma and marray very
unhappy.

I have a gal file which appears to correctly identify block, column, row, ID,
and name, and have even managed to make a SpotTypes file that shows me the
control probes.

The RGList looks like this (sorry for the large message):
> RG2
An object of class "RGList"
$R
     slide_13295067 slide_13295072 slide_13295071 slide_13295073
slide_13295075 slide_13295079 slide_13295080 slide_13295203 slide_13295068
slide_13295214
[1,]          61323          57928          57404          55737         
61890          58153          63823          53921          57871         
59289
[2,]          57955          51322          55691          60830         
48322          64418          59731          47373          53971         
54898
[3,]           1057           3361           1050           1097          
1651           1174           1349           2176           1220          
1471
[4,]           3185           7716           5754           5925          
5850           8287           8498           6246           3255          
7011
[5,]           1306            810           1069            533           
978           1485            277            326           1190           
679
     slide_13295879 slide_13295887
[1,]          58546          58522
[2,]          59005          61561
[3,]           1440           1566
[4,]          13061          12547
[5,]          24787            648
38972 more rows ...

$G
     slide_13295067 slide_13295072 slide_13295071 slide_13295073
slide_13295075 slide_13295079 slide_13295080 slide_13295203 slide_13295068
slide_13295214
[1,]          59066          58672          47495          47399         
63671          59502          53084          62982          55238         
52893
[2,]          52584          54957          39850          50818         
54542          62064          47929          57410          48840         
49985
[3,]           2443           1444            812           2001           
598           1127           2465           1558           1308          
1148
[4,]           5249           6511           2926           7372          
4312           5657          10363           8768           2464          
6809
[5,]           1662           1060            481            954           
936           1071            608            920            512           
438
     slide_13295879 slide_13295887
[1,]          57486          51338
[2,]          58792          56861
[3,]            959           1349
[4,]          12943           9490
[5,]            776            994
38972 more rows ...

$Rb
     slide_13295067 slide_13295072 slide_13295071 slide_13295073
slide_13295075 slide_13295079 slide_13295080 slide_13295203 slide_13295068
slide_13295214
[1,]            172            193            186            208           
220            174            205            237            183           
185
[2,]            168            191            183            252           
197            214            195            204            202           
259
[3,]            140            151            145            150           
157            146            151            185            142           
215
[4,]            148            144            155            153           
147            152            149            190            152           
182
[5,]            133            140            147            147           
132            143            147            185            144           
147
     slide_13295879 slide_13295887
[1,]            208            228
[2,]            210            230
[3,]            171            152
[4,]            147            143
[5,]            152            145
38972 more rows ...

$Gb
     slide_13295067 slide_13295072 slide_13295071 slide_13295073
slide_13295075 slide_13295079 slide_13295080 slide_13295203 slide_13295068
slide_13295214
[1,]            252            250            261            319           
301            285            355            588            301           
319
[2,]            247            273            280            300           
279            294            324            568            251           
310
[3,]            190            197            208            246           
219            187            265            497            223           
249
[4,]            185            198            219            247           
244            179            263            473            217           
239
[5,]            177            206            210            242           
278            196            248            501            233           
247
     slide_13295879 slide_13295887
[1,]            310            270
[2,]            287            286
[3,]            237            197
[4,]            223            222
[5,]            233            226
38972 more rows ...

$targets
[1] "slide_13295067.csv" "slide_13295072.csv" "slide_13295071.csv"
"slide_13295073.csv" "slide_13295075.csv"
7 more rows ...

$genes
  Block Column Row        ID                                        Name 
Status
1     1      1   1 mCP000073            gi|21070949|ref|NM_019639.2|_151
control
2     1      2   1 mCP000085            gi|21070949|ref|NM_019639.2|_151
control
3     1      3   1 mCT000169 NM_008512.90|chr10|-|127557334|127558231_72
control
4     1      4   1 mCP000181             gi|31981889|ref|NM_009735.2|_43
control
5     1      5   1 mCT000265    NM_011701.9|chr2|+|13576298|13576633_142
control
38971 more rows ...

$printer
$ngrid.r
[1] 12

$ngrid.c
[1] 4

$nspot.r
[1] 28

$nspot.c
[1] 29

attr(,"class")
[1] "PrintLayout"

Trying to normalize with either loess or robustspline yields:

> MA <- normalizeWithinArrays(RG2)
Error in switch(method, loess = { : printer layout information does not match
M row dimension

> MA <- normalizeWithinArrays(RG2, method="robustspline")
Loading required package: MASS
Loading required package: splines
Error in normalizeRobustSpline(object$M[, j], object$A[, j], layout, df = df, 
: 
        (subscript) logical subscript too long

Both suggest that something is amiss with my layout information, but I cannot
begin to imagine how to diagnose the exact problem.

Help!

Thanks,
Anand C. Patel, MD
Washington University School of Medicine
acpatel at usa.net



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