[R] Bioconductor and R-devel

Jennifer Lai lai at lindaspaces.com
Wed Aug 31 16:06:43 CEST 2005

   I have built R (current development version) and BioConductor 1.7 
with portland group compiler on a AMD Opteron.
When I ran qc assessment on Affymetrix latin square data set, I got the 
following output,

Loading required package: affy
Loading required package: Biobase
Loading required package: tools
Welcome to Bioconductor
         Vignettes contain introductory material.  To view,
         simply type: openVignette()
         For details on reading vignettes, see
         the openVignette help page.
Loading required package: reposTools
Welcome to 'simpleaffy' V 2.1.3                             
      Produced by The Paterson Institute for Cancer Research
      and funded by CANCER RESEARCH UK.                     
      mailto: microarray at picr.man.ac.uk                     
Background correcting
Retrieving data from AffyBatch...done.
Computing expression calls...
scaling to a TGT of 100 ...
Scale factor for: 0203_YH10_H_MCF7_r1.CEL 0.291660289301555
Scale factor for: 0203_YH11_H_MCF10A_r1.CEL 0.42025300545212
Scale factor for: 0203_YH12_H_a100MCF7_r1.CEL 0.287589038746987
Scale factor for: 0203_YH13_H_a100MCF10A_r1.CEL 0.451200408584071
Scale factor for: 0203_YH14_H_a10MCF7_r1.CEL 0.385462078301135
Scale factor for: 0203_YH15_H_a100MCF7_r2.CEL 0.284974495993646
Scale factor for: 0203_YH16_H_a100MCF7_r3.CEL 0.376484877281483
Scale factor for: 0203_YH17_H_a100MCF10A_r2.CEL 0.374087365857816
Scale factor for: 0203_YH18_H_a100MCF10A_r3.CEL 0.487207458237659
Scale factor for: 0203_YH19_H_a10MCF7_r2.CEL 0.413217979158927
Scale factor for: 0203_YH20_H_a10MCF7_r3.CEL 0.482703032325383
Scale factor for: 0203_YH21_H_a10MCF10A_r1.CEL 0.945369712044904
Scale factor for: 0203_YH22_H_a10MCF10A_r2.CEL 1.96143996386198
Scale factor for: 0203_YH23_H_a10MCF10A_r3_rescan.CEL 0.841535915879218
Scale factor for: 0203_YH24_H_MCF7_r2.CEL 0.347795838770919
Scale factor for: 0203_YH25_H_MCF7_r3.CEL 0.318539156900791
Scale factor for: 0203_YH26_H_MCF10A_r2.CEL 0.578922233010316
Scale factor for: 0203_YH27_H_MCF10A_r3.CEL 0.394833650209601
Scale factor for: 0403_YH34_H_a10MCF10A_r4.CEL 1.06804698986081
Scale factor for: 0403_YH35_H_a1MCF7_r1_2.CEL 3.5923019165673
Scale factor for: 0403_YH36_H_a1MCF7_r2.CEL 3.16130786066591
Scale factor for: 0403_YH37_H_a1MCF7_r3_2.CEL 2.01330391697437
Scale factor for: 0403_YH38_H_a1MCF10A_r1.CEL 0.923881702153984
Scale factor for: 0403_YH39_H_a1MCF10A_r2_2.CEL 2.29265379531566
Scale factor for: 0403_YH40_H_a1MCF10A_r3.CEL 4.02474777803345
Getting probe level data...
Computing p-values
Doing PMA Calls
TEST 1 : time Elapsed =  0 1 20

Background correcting
Retrieving data from AffyBatch...done.
Computing expression calls...
.........Error in FUN(X[[9]], ...) : Expecting 22283 unique probesets, 
found 22284

Can anyone advise me on how to fix this problem? I was able to run the 
same data set with gcc-compiled R2.1.1 and BioConductor 1.6 successfully.

Here is the code that I ran, if it helps to diagnose the problems.


ampli.data <- ReadAffy()

# normalize the data using call.exprs and mas5
ampli.eset <- call.exprs(ampli.data, "mas5")

# see what data is stored in ampli.eset at description@preprocssing
names(ampli.eset at description@preprocessing)

# acess each piece of information within 
ampli.eset at description@preprocessing scale factors
ampli.eset at description@preprocessing$sfs

# filenames so that the scale factors can be related to their chips
ampli.eset at description@preprocessing$filenames

# tgt is the target intensity each chip was scaled to
ampli.eset at description@preprocessing$tgt

# which version of the affy package was used
ampli.eset at description@preprocessing$affyversion

qc.data <- qc(ampli.data, ampli.eset);


# scale.factors contains a list of scale factors applied to each chip;
qc.data at scale.factors

# target is the target intensity that each chip was scaled to
qc.data at target

# percent.present is a list of the percentage of probesets called 
present on each chip;
qc.data at percent.present

# average.background, minimum.background, maximum.background are all 
lists detailing
# the average, minimum and maximum background for each chip;
qc.data at average.background

# spikes is a matrix containing normalized values for each of the spike 
colnames(qc.data at spikes)


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