Dear Matthew,
On Thu, 12 Jan 2012, Matthew Ouellette wrote:
> Dear Gordon,
>
> I feel I should have come to that conclusion myself - you're correct
> that there are missing spots. ?However, this is not the result of
> software removing blank spots; it is in fact the way we printed the
> array. ?Each block consists of 6 rows x 14 columns, but the 6th row
> only has spots in columns 1 and 2 (i.e. there are only 2 spots on
row
> 6 in each block). ?This layout is the result of spotting 384 probes
in
> the smallest area possible in order to cut down the amount of RT
> reagents needed to produce significant results.
>
> As I mentioned earlier, I am very new to R. ?I am in the process of
> attempting to use the block count variable you suggested, however
I'm
> having difficulties adjusting it to the code you suggested in 2005.
> How would I modify the following to fit my particular array?
>
> for (b in 1:48) {
> i <- RG$genes$Block==b
> MA2 <- normalizeWithinArrays(RG[i,],method="loess")
> if(b==1)
> MA <- MA2
> else
> MA <- rbind(MA,MA2)
> }
Replace "48" with "16" and "RG$genes$Block" with "block".
> As for the the input files, I have attempted to use:
>
> RG <-read.maimages(targets, source="scanarrayexpress", sep=",")
>
> on unedited files, but the following warnings come up (when
analyzing
> 15 unedited array files this time):
>
>> RG<-read.maimages(targets, source="scanarrayexpress", sep=",")
> Read 01-13_B.csv
> Read 01-13_M.csv
> Read 01-13_T.csv
> Read 01-14_B.csv
> Read 01-14_M.csv
> Read 01-14_T.csv
> Read 01-15_B.csv
> Read 01-15_M.csv
> Read 01-15_T.csv
> Read 01-16_B.csv
> Read 01-16_M.csv
> Read 01-16_T.csv
> Read 01-17_B.csv
> Read 01-17_M.csv
> Read 01-17_T.csv
> There were 45 warnings (use warnings() to see them)
>> warnings()
> Warning messages:
> 1: In grep(a, txt) : input string 1 is invalid in this locale
> 2: In grep(a, txt) : input string 1 is invalid in this locale
> 3: In grep(a, txt) : input string 1 is invalid in this locale
> 4: In grep(a, txt) : input string 1 is invalid in this locale
> 5: In grep(a, txt) : input string 1 is invalid in this locale
> 6: In grep(a, txt) : input string 1 is invalid in this locale
> 7: In grep(a, txt) : input string 1 is invalid in this locale
> 8: In grep(a, txt) : input string 1 is invalid in this locale
> 9: In grep(a, txt) : input string 1 is invalid in this locale
> 10: In grep(a, txt) : input string 1 is invalid in this locale
> [... to 45]
This is most likely caused by the fact that your copy of R is compiled
for
a different language than that used by the software used to write your
data. Eg., it could be that your R is American English and but the
files
were written using an extended French alphabet, so your files contain
non-english letters.
Typing sessionInfo() will reveal the language (locale) your version of
R
is compiled for.
> I have contacted a co-worker about this problem and he claims that
he
> doesn't get this error when using R in Windows XP (I am currently
> using Mac OS X). At first, I thought these errors would skew my
> results so I opted to edit the files myself just to get the hang of
> limma.
Nothing to do with Windows or Mac. Probably doesn't affect your limma
results.
Best wishes
Gordon
> I appreciate your help,
>
> Matthew
>
> On Wed, Jan 11, 2012 at 11:52 PM, Gordon K Smyth <smyth at="" wehi.edu.au=""> wrote:
>>
>> Dear Matthew,
>>
>> This question hasn't been asked for many years! ?It used to be
quite a common question, see for example:
>>
>>
https://stat.ethz.ch/pipermail/bioconductor/2005-July/009886.html
>>
>> The problem is not that you have an extra row, but rather than you
have too few rows. ?Your arrays have 16 blocks (4 x 4) with 6 rows and
14 columns of spots in each block. ?So limma assumes your arrays to
have 4x4x6x14 = 1344 spots, but your files actually contain only 1152
rows of data. ?The reason is almost certainly that a number of empty
spots have been removed from the files.
>>
>> One easy workaround is simply to do global loess instead of print-
tip-loess normalization:
>>
>> ?MA <- normalizeWithinArrays(RG, method="loess")
>>
>> Another workaround is to make up a block count variable:
>>
>> ?block <- 4*(RG$genes[,"Array Row"]-1) + RG$genes[,"Array Column"]
>>
>> and then to use the solution that I suggested back in July 2005.
>>
>>
>> With respect to the deleting of 74 lines of headers and so forth,
have you tried simply using
>>
>> ?RG <-read.maimages(targets, source="scanarrayexpress", sep=",")
>>
>> using your original unedited files? ?The whole reason for having a
"scanarrayexpress" method for read.maimages() is that it takes care of
all the editing and reading for you.
>>
>> Best wishes
>> Gordon
>>
>>
>>> Date: Tue, 10 Jan 2012 14:34:53 -0500
>>> From: Matthew Ouellette <ouellet5 at="" uwindsor.ca="">
>>> To: bioconductor at r-project.org
>>> Subject: [BioC] Problems normalizing scanarray express data with
limma
>>>
>>> Hello,
>>>
>>> I'm having trouble analyzing my custom arrays with limma. ?I've
searched
>>> the archives and I seem to be running into a similar problem that
was
>>> previously dealt with here (
>>>
https://stat.ethz.ch/pipermail/bioconductor/2005-October/010482.html).
>>>
>>> I'm also using outputs from a scanarray express, although I've
modified my
>>> .csv's accordingly and removed the final line of useless data as
indicated
>>> in the archives. ?Also, being an R newbie I wasn't sure how to
tell R that
>>> my data started after some 74 lines of headers (output info from
the
>>> scanner), so I deleted those headers out as well (and input
$printer info
>>> manually), leaving only a header for the columns of intensity
data. ? For
>>> simplicities sake I've pasted below a shortened session of what
I'm trying
>>> to do (my apologies for the lengthy e-mail). ?I appreciate the
help and
>>> comments.
>>>
>>>
>>>
>>> R version 2.14.0 (2011-10-31)
>>> Copyright (C) 2011 The R Foundation for Statistical Computing
>>> ISBN 3-900051-07-0
>>> Platform: i386-apple-darwin9.8.0/i386 (32-bit)
>>> [R.app GUI 1.42 (5933) i386-apple-darwin9.8.0]
>>>
>>>> setwd("***")
>>>> library(limma)
>>>> targets<-readTargets()
>>>> RG <-read.maimages(targets,
source="scanarrayexpress",annotation=c("Array
>>>
>>> Row", "Array Column", "Spot Row", "Spot Column", "Name", "ID"),
>>> other.columns=c("Ch1 SignalNoiseRatio", "Ch2 SignalNoiseRatio"),
sep=",")
>>> Read 01-13_B.csv
>>> Read 01-13_M.csv
>>> Read 01-13_T.csv
>>>>
>>>> RG$printer <-getLayout2("ChinookBOT.gal")
>>>> spottypes<-readSpotTypes()
>>>> RG$genes$Status<- controlStatus(spottypes, RG)
>>>
>>> Matching patterns for: Name
>>> Found 1116 oligo
>>> Found 21 blank
>>> Found 15 serial
>>> Setting attributes: values Color
>>>>
>>>> show(RG)
>>>
>>> An object of class "RGList"
>>> $G
>>> ? ?01-13_B 01-13_M 01-13_T
>>> [1,] ? ? 102 ? ? 119 ? ? 239
>>> [2,] ? ? 100 ? ? 122 ? ? 339
>>> [3,] ? ? 102 ? ? 135 ? ? 251
>>> [4,] ? ? ?90 ? ? 112 ? ? 242
>>> [5,] ? ? 110 ? ? 141 ? ? 239
>>> 1147 more rows ...
>>>
>>> $Gb
>>> ? ?01-13_B 01-13_M 01-13_T
>>> [1,] ? ? ?89 ? ? ?94 ? ? 147
>>> [2,] ? ? ?88 ? ? ?84 ? ? 181
>>> [3,] ? ? ?88 ? ? ?91 ? ? 161
>>> [4,] ? ? ?92 ? ? ?90 ? ? 175
>>> [5,] ? ? ?86 ? ? ?87 ? ? 154
>>> 1147 more rows ...
>>>
>>> $R
>>> ? ?01-13_B 01-13_M 01-13_T
>>> [1,] ? ? 120 ? ? 678 ? ? 202
>>> [2,] ? ? 154 ? ? 610 ? ? 312
>>> [3,] ? ? 146 ? ? 614 ? ? 306
>>> [4,] ? ? 108 ? ? 654 ? ? 310
>>> [5,] ? ? 122 ? ? 710 ? ? 291
>>> 1147 more rows ...
>>>
>>> $Rb
>>> ? ?01-13_B 01-13_M 01-13_T
>>> [1,] ? ? 108 ? ? 119 ? ? 135
>>> [2,] ? ? 109 ? ? 137 ? ? 159
>>> [3,] ? ? 113 ? ? 124 ? ? 169
>>> [4,] ? ? 115 ? ? 124 ? ? 180
>>> [5,] ? ? 119 ? ? 104 ? ? 159
>>> 1147 more rows ...
>>>
>>> $targets
>>> ? ?FileName Cy3 Cy5
>>> 1 01-13_B.csv ?B1 ?B2
>>> 2 01-13_M.csv ?M1 ?M2
>>> 3 01-13_T.csv ?T1 ?T2
>>>
>>> $genes
>>> ?Array Row Array Column Spot Row Spot Column ? ? Name ? ? ?ID
Status
>>> 1 ? ? ? ? 1 ? ? ? ? ? ?1 ? ? ? ?1 ? ? ? ? ? 1 HEATH049 Gene A4
?oligo
>>> 2 ? ? ? ? 1 ? ? ? ? ? ?1 ? ? ? ?1 ? ? ? ? ? 2 HEATH049 Gene A4
?oligo
>>> 3 ? ? ? ? 1 ? ? ? ? ? ?1 ? ? ? ?1 ? ? ? ? ? 3 HEATH049 Gene A4
?oligo
>>> 4 ? ? ? ? 1 ? ? ? ? ? ?1 ? ? ? ?1 ? ? ? ? ? 4 HEATH113 Gene A8
?oligo
>>> 5 ? ? ? ? 1 ? ? ? ? ? ?1 ? ? ? ?1 ? ? ? ? ? 5 HEATH113 Gene A8
?oligo
>>> 1147 more rows ...
>>>
>>> $source
>>> [1] "scanarrayexpress"
>>>
>>> $other
>>> $Ch1 SignalNoiseRatio
>>> ? ?01-13_B 01-13_M 01-13_T
>>> [1,] ? ?3.06 ? ?2.55 ? ?3.02
>>> [2,] ? ?2.72 ? ?3.06 ? ?2.35
>>> [3,] ? ?2.68 ? ?3.60 ? ?3.34
>>> [4,] ? ?2.51 ? ?3.12 ? ?0.95
>>> [5,] ? ?3.33 ? ?3.82 ? ?2.66
>>> 1147 more rows ...
>>>
>>> $Ch2 SignalNoiseRatio
>>> ? ?01-13_B 01-13_M 01-13_T
>>> [1,] ? ?2.31 ? 12.41 ? ?2.85
>>> [2,] ? ?2.42 ? 11.82 ? ?3.57
>>> [3,] ? ?2.66 ? 11.71 ? ?4.14
>>> [4,] ? ?1.75 ? 14.41 ? ?0.65
>>> [5,] ? ?2.09 ? 15.90 ? ?4.62
>>> 1147 more rows ...
>>>
>>>
>>> $printer
>>> $ngrid.r
>>> [1] 4
>>>
>>> $ngrid.c
>>> [1] 4
>>>
>>> $nspot.r
>>> [1] 6
>>>
>>> $nspot.c
>>> [1] 14
>>>
>>>
>>>> MA<- normalizeWithinArrays(RG)
>>>
>>> Error in normalizeWithinArrays(RG) :
>>> ?printer layout information does not match M row dimension
>>>
>>>
>
>
> --
> Matthew Ouellette, M.Sc. Candidate
> Great Lakes Institute for Environmental Research
> University of Windsor
> 401 Sunset Ave., Windsor, ON, N9B 3P4
> Phone:?(519) 253-3000, Ext 4248
> Fax:?(519) 971-3616
> Email:?ouellet5 at uwindsor.ca
>
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