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Crispin Miller
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@crispin-miller-264
Last seen 10.2 years ago
Hi,
I think Jennifer and I got this fixed a few days ago. Hopefully the
new
version in the devl branch solves this problem.
Crispin
-----Original Message-----
From: bioconductor-bounces@stat.math.ethz.ch
[mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of
Jennifer
Lai
Sent: 31 August 2005 15:28
To: bioconductor at stat.math.ethz.ch
Subject: [BioC] affymetrix latin square
Hi,
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.
http://bioinformatics.picr.man.ac.uk/simpleaffy mailto:
microarray at picr.man.ac.uk Background correcting
Retrieving data from AffyBatch...done.
Computing expression calls...
.........................done.
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.
library(simpleaffy);
library(affy);
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);
slotNames(qc.data);
# 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
controls
colnames(qc.data at spikes)
Thanks,
Jennifer
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