[BioC] BioNet - interpretation of node score (Eva Benito Garagorri)
Daniela Beißer
daniela.beisser at biozentrum.uni-wuerzburg.de
Sat Sep 25 15:02:11 CEST 2010
Dear Eva,
The likelihood ratio score used in BioNet is a monotone transformation of
the p-values. In your case the node scores measure the significance of
differential expression of the genes. Thus the higher the node score the
more significant the gene and vice versa. Negative scores denote nodes that
are regarded as not significant given a certain FDR threshold. If the FDR
threshold is changed positive scoring nodes can of course become negative.
Analogously, an edge between negative scoring nodes represents not
differentially expressed interacting genes.
If you have further question please feel free to contact us.
Best wishes,
Marcus and Daniela
-----Ursprüngliche Nachricht-----
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When replying, please edit your Subject line so it is more specific
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Today's Topics:
1. Re: Gating with an ellipsoidGate (Roger Leigh)
2. Re: Gating with an ellipsoidGate (Roger Leigh)
3. Re: probeAnno for tilingArray package. (Wolfgang Huber)
4. Comparing 2 GEO datasets (Yogesh)
5. Oligo package crlmm method (Zhu, Julie)
6. Re: Oligo package crlmm method (Benilton Carvalho)
7. Re: Oligo package crlmm method (Zhu, Julie)
8. Re: Comparing 2 GEO datasets (Sean Davis)
9. Re: Comparing 2 GEO datasets (Yogesh)
10. Re: Oligo package crlmm method (Zhu, Julie)
11. Re: Agi4x44PreProcess- RSQLite driver: (RS_SQLite_fetch:
failed first step: disk I/O error) (Brown, Joseph)
12. Re: Comparing 2 GEO datasets (Sean Davis)
13. Re: Comparing 2 GEO datasets (Yogesh)
14. Re: probeAnno for tilingArray package.
(sohkhan at notes.cc.sunysb.edu)
15. Querying clustering in heatmap.2 (Elizabeth Ashley)
16. BioNet - interpretation of node score (Eva Benito Garagorri)
17. Re: Gating with an ellipsoidGate (Josef Spidlen)
18. e-LICO multi-omics prediction challenge with background
knowledge on Obstructive Nephropathy (Adam Woznica)
19. Re: Querying clustering in heatmap.2 (Steve Lianoglou)
----------------------------------------------------------------------
Message: 1
Date: Wed, 15 Sep 2010 12:24:06 +0100
From: Roger Leigh <rleigh at codelibre.net>
To: Josef Spidlen <jspidlen at bccrc.ca>
Cc: "bioconductor at stat.math.ethz.ch" <bioconductor at stat.math.ethz.ch>
Subject: Re: [BioC] Gating with an ellipsoidGate
Message-ID: <4C90ACD6.4090600 at codelibre.net>
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
Dear Josef,
Many thanks, the speadsheet was most helpful!
I did try creating a covariance matrix from separate scaling and
rotation matrices (below), but this didn't work, I suppose because they
are too simple--operating in Euclidean space rather than Mahalanobis space.
cov.matrix.simple <- function (a, b, angle) {
theta <- angle * (pi/180)
R <- matrix(c(cos(theta), -sin(theta), sin(theta), cos(theta)),
byrow=TRUE, ncol=2)
S <- matrix(c(a, 0, 0, b), byrow=TRUE, ncol=2)
S%*%R
}
Using your spreadsheet, I've created a macro to create a covariance
matrix in R from a, b and an angle, which I've verified to match the
results shown in your spreadsheet:
cov.matrix <- function (a, b, angle) {
theta <- angle * (pi/180)
c1 <- ((cos(theta)^2)/a^2) + ((sin(theta)^2)/b^2)
c2 <- sin(theta) * cos(theta) * ((1/a^2) - (1/b^2))
c3 <- ((sin(theta)^2)/a^2) + ((cos(theta)^2)/b^2)
m1 <- matrix(c(c1, c2, c2, c3), byrow=TRUE, ncol=2)
m2 <- solve(m1)
m2
}
This appears to work well when rotation is not involved. However, as
soon as I try to add rotation, it blows up:
library(flowCore)
library(flowViz)
library(flowUtils)
cov.matrix <- function (a, b, angle) {
theta <- angle * (pi/180)
c1 <- ((cos(theta)^2)/a^2) + ((sin(theta)^2)/b^2)
c2 <- sin(theta) * cos(theta) * ((1/a^2) - (1/b^2))
c3 <- ((sin(theta)^2)/a^2) + ((cos(theta)^2)/b^2)
m1 <- matrix(c(c1, c2, c2, c3), byrow=TRUE, ncol=2)
m2 <- solve(m1)
m2
}
d <- read.FCS("0isotype.fcs", alter.names=TRUE)
d <- transform(d, `SS.Log` = log10(`SS.Log`))
# No rotation
cov <- cov.matrix(20000, 0.4, 0)
colnames(cov) <- c("FS.Lin", "SS.Log")
rownames(cov) <- c("FS.Lin", "SS.Log")
mean <- c("FS.Lin"=40000, "SS.Log"=2.8)
cells <- ellipsoidGate(filterId="CellGate", .gate=cov, mean=mean)
print(cov)
pdf("test.pdf", width=8, height=8, pointsize=12)
print(xyplot(`SS.Log` ~ `FS.Lin`, d, filter=cells, xlab="FS",
ylab=expression(log[10]~(SS))))
dev.off()
# Now repeat with a 20 degree rotation...
cov <- cov.matrix(20000, 0.4, 20)
colnames(cov) <- c("FS.Lin", "SS.Log")
rownames(cov) <- c("FS.Lin", "SS.Log")
mean <- c("FS.Lin"=40000, "SS.Log"=2.8)
cells <- ellipsoidGate(filterId="CellGate", .gate=cov, mean=mean)
print(cov)
pdf("test-rotate.pdf", width=8, height=8, pointsize=12)
print(xyplot(`SS.Log` ~ `FS.Lin`, d, filter=cells, xlab="FS",
ylab=expression(log[10]~(SS))))
dev.off()
I've put the source data, script and results at:
http://www-users.york.ac.uk/~rl522/flowcore-test/
http://www-users.york.ac.uk/~rl522/flowcore-test/test.pdf
http://www-users.york.ac.uk/~rl522/flowcore-test/test-rotate.pdf
You can see that while an ellipse is drawn correctly in the first
instance, when we add a 20 degree rotation, it's completely screwed.
I'm not sure if this is due to the extreme differences in the x and y
dimensions, which alter the length of a and b, or for some other reason.
Many thanks,
Roger
On 14/09/2010 18:00, Josef Spidlen wrote:
> Hi Roger,
> I am not the author of flowCore but I believe the ellipsoid gate
> constructor takes covariance matrices since this is used in the
> Gating-ML specification. Mathematically, this is a nice way to specify
> ellipsoids in multidimensional space.
>
> I have posted a simple spreadsheet that allows you to convert the
> representation of an ellipse by half-axes, rotation and centre point to
> covariance matrix, mean (= centre point), and distance square (=1 for
> this case). Please follow this link for download:
>
http://sourceforge.net/projects/flowcyt/files/Gating-ML/Gating-ML%201.5/Elli
pseCalculations.xls/download
>
> I hope this addresses your issues; let me know if further help is needed.
>
> Unfortunately, I'll have to leave it up to the flowCore/flowViz authors
> to get back to you with your other questions.
>
> Cheers,
> Josef
>
>> Message: 6
>> Date: Mon, 13 Sep 2010 15:51:55 +0100
>> From: Roger Leigh<rleigh at codelibre.net>
>> To: bioconductor at stat.math.ethz.ch
>> Subject: [BioC] FlowCore/FlowViz issues
>> Message-ID:<20100913145155.GW6128 at codelibre.net>
>> Content-Type: text/plain; charset=utf-8
>>
>> Hi,
>>
>> [Apologies if this is delivered twice; my initial mail didn't
>> appear to be accepted for several hours, and I didn't see any
>> failure message; does the list object to GPG signatures?]
>>
>> I've just started to use FlowCore/FlowViz to analyse some of my
>> flow cytometry data, and ran into a few problems. I'm hoping
>> that you might be able to point me in the right direction!
>>
>> I've been very pleased with it so far, and have got some nice
>> plots and stats out of it, but I'm sure I'm doing some things
>> very inefficiently and/or incorrectly!
>>
>> [I'm using R version 2.11.1 (2010-05-31) on x86_64-pc-linux-gnu
>> (Debian GNU/Linux) with current Bioconductor packages)]
>>
>>
>> 1) Gating with an ellipsoidGate
>>
>> cov<- matrix(c(400000000, 0, 0, 0.08), ncol=2,
>> dimnames=list(c("FS.Lin", "SS.Log"), c("FS.Lin", "SS.Log")))
>> mean<- c("FS.Lin"=32000, "SS.Log"=2.8)
>> cells<- ellipsoidGate(filterId="CellGate", .gate=cov, mean=mean)
>>
>> I want to select my cells using an ellipsoid gate on forward- and side-
>> scatter plots. In the above situation, they lie in a region where
>> FS=32000?10000 and log??(SS)=2.8?0.5. However, the values in the
>> covariance matrix don't match the dimensions; is there any explanation
>> regarding how to construct a covariance matrix from the actual
>> dimension I want (I got the above by trial and error until it fitted
>> nicely--I'm afraid I know little about these matrices).
>>
>> In some plots I'd also like to rotate the ellipse, but I'm not sure
>> how to put this into the matrix, if that's the way to do things.
>> Is this possible?
>>
>> Is there an alternative constructor to create a gate from real
>> dimensions?
>>
>>
>>
>> Many thanks for all your help,
>> Roger
>>
>> --
>> .''`. Roger Leigh
>> : :' : Debian GNU/Linux http://people.debian.org/~rleigh/
>> `. `' Printing on GNU/Linux? http://gutenprint.sourceforge.net/
>> `- GPG Public Key: 0x25BFB848 Please GPG sign your mail.
>>
>>
>
------------------------------
Message: 2
Date: Wed, 15 Sep 2010 12:37:40 +0100
From: Roger Leigh <rleigh at codelibre.net>
To: bioconductor at stat.math.ethz.ch
Cc: jspidlen at bccrc.ca
Subject: Re: [BioC] Gating with an ellipsoidGate
Message-ID: <4C90B004.1070405 at codelibre.net>
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
On 15/09/2010 12:24, Roger Leigh wrote:
> This appears to work well when rotation is not involved. However, as
> soon as I try to add rotation, it blows up:
>
> library(flowCore)
> library(flowViz)
> library(flowUtils)
>
> cov.matrix <- function (a, b, angle) {
> theta <- angle * (pi/180)
>
> c1 <- ((cos(theta)^2)/a^2) + ((sin(theta)^2)/b^2)
> c2 <- sin(theta) * cos(theta) * ((1/a^2) - (1/b^2))
> c3 <- ((sin(theta)^2)/a^2) + ((cos(theta)^2)/b^2)
>
> m1 <- matrix(c(c1, c2, c2, c3), byrow=TRUE, ncol=2)
> m2 <- solve(m1)
>
> m2
> }
>
> d <- read.FCS("0isotype.fcs", alter.names=TRUE)
> d <- transform(d, `SS.Log` = log10(`SS.Log`))
>
> # No rotation
> cov <- cov.matrix(20000, 0.4, 0)
> colnames(cov) <- c("FS.Lin", "SS.Log")
> rownames(cov) <- c("FS.Lin", "SS.Log")
> mean <- c("FS.Lin"=40000, "SS.Log"=2.8)
> cells <- ellipsoidGate(filterId="CellGate", .gate=cov, mean=mean)
> print(cov)
> pdf("test.pdf", width=8, height=8, pointsize=12)
> print(xyplot(`SS.Log` ~ `FS.Lin`, d, filter=cells, xlab="FS",
> ylab=expression(log[10]~(SS))))
> dev.off()
>
> # Now repeat with a 20 degree rotation...
> cov <- cov.matrix(20000, 0.4, 20)
> colnames(cov) <- c("FS.Lin", "SS.Log")
> rownames(cov) <- c("FS.Lin", "SS.Log")
> mean <- c("FS.Lin"=40000, "SS.Log"=2.8)
> cells <- ellipsoidGate(filterId="CellGate", .gate=cov, mean=mean)
> print(cov)
>
> pdf("test-rotate.pdf", width=8, height=8, pointsize=12)
> print(xyplot(`SS.Log` ~ `FS.Lin`, d, filter=cells, xlab="FS",
> ylab=expression(log[10]~(SS))))
> dev.off()
>
> I've put the source data, script and results at:
> http://www-users.york.ac.uk/~rl522/flowcore-test/
>
> http://www-users.york.ac.uk/~rl522/flowcore-test/test.pdf
> http://www-users.york.ac.uk/~rl522/flowcore-test/test-rotate.pdf
>
> You can see that while an ellipse is drawn correctly in the first
> instance, when we add a 20 degree rotation, it's completely screwed. I'm
> not sure if this is due to the extreme differences in the x and y
> dimensions, which alter the length of a and b, or for some other reason.
cov <- cov.matrix(20000, 0.4, 20)
While this gives what looks like an almost entirely vertical line, using
a much smaller angle
cov <- cov.matrix(20000, .25, 0.0005)
actually results in a sensible rotation, of about 20 degrees. So it
looks like it works, but the scaling of the angle is wrong--it's far too
sensitive. I'm correctly converting from degrees to radians, so I'm not
sure why 8.7e-6 radians actually results in a rotation of ~0.35 radians!
Regards,
Roger
------------------------------
Message: 3
Date: Wed, 15 Sep 2010 15:25:50 +0200
From: Wolfgang Huber <whuber at embl.de>
To: sohkhan at notes.cc.sunysb.edu
Cc: bioconductor at stat.math.ethz.ch
Subject: Re: [BioC] probeAnno for tilingArray package.
Message-ID: <4C90C95E.6070209 at embl.de>
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
On Sep/14/10 7:36 PM, sohkhan at notes.cc.sunysb.edu wrote:
> Thank you Wolfgang.
> I corrected the chr parameter as suggested by Noah. segChrom runs with
> strand=NA. Now, I have question about the probeAnno creation by
> bpmapToProbeAnno(). Does the function treat 0's as "-" and 1's "+" strand.
> I have just one BPMAP file for S.pombe from Affymetrix which contains
> 0's and 1's in the strand column.
Why don't you just try and report problems, if any?
Wolfgang
> Thanks again.
> -Sohail
>
>
>
> From: Wolfgang Huber <whuber at embl.de>
> To: bioconductor at stat.math.ethz.ch
> Date: 09/11/2010 08:15 AM
> Subject: Re: [BioC] probeAnno for tilingArray package.
> Sent by: bioconductor-bounces at stat.math.ethz.ch
> ------------------------------------------------------------------------
>
>
>
> Dear Sohail
>
> in R, the character string "NA" is different from the value NA. Try with
> supplying the second one for the argument 'strands'. Also, please make
> sure that the 'chr' argument is set to the right value, the default
> (1:17) is likely not to work with S.pombe. You can see what the
> chromosome names are in your organism by inspecting the probeAnno object.
>
> Best wishes
> Wolfgang
>
> On Sep/8/10 10:33 PM, sohkhan at notes.cc.sunysb.edu wrote:
> > Hi all,
> >
> > I am trying to use the "tilingArray" package to analyze Affymetrix
> S.pombe
> > tiling arrays. I downloaded the .bpmap file from Affymetrix's website,
> > and created a probeAnno object by bpmapToProbeAnno().
> > However, I am getting the following error when I try to segment the
data
> > by segChrom().
> >
> >> segdf<-segChrom(cels,probeAnno,strands="NA")
> > Running 'segment' on chromosome 1.NAError in probeAnno[w] :
> > No mapping '1.NA.start' in this 'probeAnno' object.
> >
> >> sessionInfo()
> > R version 2.11.1 (2010-05-31)
> > x86_64-apple-darwin9.8.0
> >
> > locale:
> > [1] en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8
> >
> > attached base packages:
> > [1] grid stats graphics grDevices utils datasets methods
> > base
> >
> > other attached packages:
> > [1] davidTiling_1.2.12 GO.db_2.4.1 RSQLite_0.9-2 DBI_0.2-5
> > AnnotationDbi_1.10.2 tilingArray_1.26.0 pixmap_0.4-10 Starr_1.4.4
> >
> > [9] affy_1.26.1 Ringo_1.12.0 Matrix_0.999375-39
> > lattice_0.18-8 limma_3.4.4 RColorBrewer_1.0-2 Biobase_2.8.0
> > affxparser_1.20.0
> >
> > loaded via a namespace (and not attached):
> > [1] affyio_1.16.0 annotate_1.26.1 genefilter_1.30.0
> > MASS_7.3-6 preprocessCore_1.10.0 pspline_1.0-14 splines_2.11.1
> > strucchange_1.4-1
> > [9] survival_2.35-8 tools_2.11.1 vsn_3.16.0 xtable_1.5-6
> >
> >
> > I am wondering if I used the correct .bpmap file??
> > Thanks for any suggestion/advice.
> >
> > -Sohail
> > SBU, NY
> >>
> > [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > Bioconductor mailing list
> > Bioconductor at stat.math.ethz.ch
> > https://stat.ethz.ch/mailman/listinfo/bioconductor
> > Search the archives:
> http://news.gmane.org/gmane.science.biology.informatics.conductor
>
> --
>
>
> Wolfgang Huber
> EMBL
> http://www.embl.de/research/units/genome_biology/huber
>
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives:
> http://news.gmane.org/gmane.science.biology.informatics.conductor
>
--
Wolfgang Huber
EMBL
http://www.embl.de/research/units/genome_biology/huber
------------------------------
Message: 4
Date: Wed, 15 Sep 2010 10:48:11 -0400
From: Yogesh <yogeshp08 at gmail.com>
To: Bioconductor-R Mailing List <bioconductor at stat.math.ethz.ch>
Subject: [BioC] Comparing 2 GEO datasets
Message-ID:
<AANLkTimq2fyrdrvv=n2-EAW97-aP=GXfUuyjgiGEo92R at mail.gmail.com>
Content-Type: text/plain
Hello,
I want to compare two GEO datasets based on the time series data. I want to
be able to draw some visual highlighting/showing the difference in the
expression of the two sets.
Can some one please guide me on how to go about it?
Thanks a lot.
-Yogesh
[[alternative HTML version deleted]]
------------------------------
Message: 5
Date: Wed, 15 Sep 2010 11:27:55 -0400
From: "Zhu, Julie" <Julie.Zhu at umassmed.edu>
To: "bioconductor at stat.math.ethz.ch" <bioconductor at stat.math.ethz.ch>
Subject: [BioC] Oligo package crlmm method
Message-ID: <C8B65E3B.3370%julie.zhu at umassmed.edu>
Content-Type: text/plain; charset=us-ascii
Hi,
I am using the crlmm function in Oligo package to make SNP calls. I
encountered the following segfault error. Could you please let me know what
could be the cause and how to tackle the problem?
Thanks so much for your help!
Kind regards,
Julie
library("oligo")
library("pd.mapping250k.sty")
fullFilenames <- list.celfiles("Sty_CEL_CML", full.names = TRUE)
outputDir <- file.path(getwd(), "crlmmResults_StyCML")
if (!file.exists(outputDir)) crlmm(fullFilenames, outputDir)
*** caught segfault ***
address 0x12de80000, cause 'memory not mapped'
Traceback:
1: .Call("R_affx_get_cel_file_header", filename, PACKAGE = "affxparser")
2: readCelHeader(x)
3: FUN(c("Sty_CEL_CML/CML-#1-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#1-CP-250ksty.CEL", "Sty_CEL_CML/CML-#10-AP-250ksty.CEL",
"Sty_CEL_CML/CML-#10-CP-250ksty.CEL", "Sty_CEL_CML/CML-#11-AP-250ksty.CEL",
"Sty_CEL_CML/CML-#11-CP-250ksty.CEL", "Sty_CEL_CML/CML-#12-AP-250ksty.CEL",
"Sty_CEL_CML/CML-#12-CP-250ksty.CEL", "Sty_CEL_CML/CML-#12-CP2-250ksty.CEL",
"Sty_CEL_CML/CML-#13-CP-250ksty.CEL", "Sty_CEL_CML/CML-#13-CP2-250ksty.CEL",
"Sty_CEL_CML/CML-#14-BC-250ksty.CEL", "Sty_CEL_CML/CML-#14-Rem-250ksty.CEL",
"Sty_CEL_CML/CML-#15-BC-250ksty.CEL", "Sty_CEL_CML/CML-#15-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#15-CP2-250ksty.CEL", "Sty_CEL_CML/CML-#16-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#16-BC-GL-250ksty.CEL",
"Sty_CEL_CML/CML-#16-CP-250ksty.CEL", "Sty_CEL_CML/CML-#16-CP2-250ksty.CEL",
"Sty_CEL_CML/CML-#17-AP-250ksty.CEL", "Sty_CEL_CML/CML-#17-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#18-BC-250ksty.CEL", "Sty_CEL_CML/CML-#19-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#19-BC-GL-250ksty.CEL",
"Sty_CEL_CML/CML-#19-CP-250ksty.CEL", "Sty_CEL_CML/CML-#2-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#2-CP2-250ksty.CEL", "Sty_CEL_CML/CML-#20-AP-250ksty.CEL",
"Sty_CEL_CML/CML-#20-BC-250ksty.CEL", "Sty_CEL_CML/CML-#20-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#21-CP-250ksty.CEL", "Sty_CEL_CML/CML-#21-CP2-250ksty.CEL",
"Sty_CEL_CML/CML-#22-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#22-BC-GL-250ksty.CEL",
"Sty_CEL_CML/CML-#22-CP-250ksty.CEL", "Sty_CEL_CML/CML-#23-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#23-BC-GL-250ksty.CEL",
"Sty_CEL_CML/CML-#23-CP-250ksty.CEL", "Sty_CEL_CML/CML-#3-AP-250ksty.CEL",
"Sty_CEL_CML/CML-#3-BC-250ksty.CEL", "Sty_CEL_CML/CML-#4-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#4-CP-250ksty.CEL", "Sty_CEL_CML/CML-#4-Rem-250ksty.CEL",
"Sty_CEL_CML/CML-#5-BC-250ksty.CEL", "Sty_CEL_CML/CML-#5-BC-GL-250ksty.CEL",
"Sty_CEL_CML/CML-#5-Rem-250ksty.CEL", "Sty_CEL_CML/CML-#6-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#6-BC-GL-250ksty.CEL", "Sty_CEL_CML/CML-#6-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#7-BC-250ksty.CEL", "Sty_CEL_CML/CML-#7-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#8-AP-250ksty.CEL", "Sty_CEL_CML/CML-#8-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#9-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#9-BC-GL-250ksty.CEL")[[16L]], ...)
4: lapply(X, FUN, ...)
5: sapply(filenames, function(x) readCelHeader(x)$chiptype)
6: justCRLMMv3(filenames, outdir, batch_size = batch_size, recalibrate =
recalibrate, minLLRforCalls = minLLRforCalls, balance = balance, verbose
= verbose)
7: crlmm(fullFilenames, outputDir)
Possible actions:
1: abort (with core dump, if enabled)
2: normal R exit
3: exit R without saving workspace
4: exit R saving workspace
Selection:
sessionInfo()
R version 2.11.1 (2010-05-31)
x86_64-apple-darwin9.8.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] pd.mapping250k.sty_1.0.0 RSQLite_0.9-2 DBI_0.2-5
[4] oligo_1.12.2 oligoClasses_1.10.0 Biobase_2.8.0
loaded via a namespace (and not attached):
[1] affxparser_1.20.0 affyio_1.16.0 Biostrings_2.16.9
IRanges_1.6.11
[5] preprocessCore_1.10.0 splines_2.11.1
------------------------------
Message: 6
Date: Wed, 15 Sep 2010 16:43:18 +0100
From: Benilton Carvalho <beniltoncarvalho at gmail.com>
To: "Zhu, Julie" <Julie.Zhu at umassmed.edu>
Cc: "bioconductor at stat.math.ethz.ch" <bioconductor at stat.math.ethz.ch>
Subject: Re: [BioC] Oligo package crlmm method
Message-ID:
<AANLkTim7vw2YK+ZE_xjsgkGp5v32dYO67uxy774rkNaH at mail.gmail.com>
Content-Type: text/plain; charset=ISO-8859-1
Start a new session of R and try the following:
cels = list.files("Sty_CEL_CML", pattern="CEL$", full=TRUE)
library(affxparser)
table(sapply(cels, function(x) readCelHeader(x)[["chiptype"]]))
and let me know what you get.
b
On 15 September 2010 16:27, Zhu, Julie <Julie.Zhu at umassmed.edu> wrote:
> Hi,
>
> I am using the crlmm function in Oligo package to make SNP calls. I
> encountered the following segfault error. Could you please let me know
what
> could be the cause and how to tackle the problem?
>
> Thanks so much for your help!
>
> Kind regards,
>
> Julie
>
> library("oligo")
> library("pd.mapping250k.sty")
> fullFilenames <- list.celfiles("Sty_CEL_CML", full.names = TRUE)
> outputDir <- file.path(getwd(), "crlmmResults_StyCML")
> if (!file.exists(outputDir)) crlmm(fullFilenames, outputDir)
>
> ?*** caught segfault ***
> address 0x12de80000, cause 'memory not mapped'
>
> Traceback:
> ?1: .Call("R_affx_get_cel_file_header", filename, PACKAGE = "affxparser")
> ?2: readCelHeader(x)
> ?3: FUN(c("Sty_CEL_CML/CML-#1-BC-250ksty.CEL",
> "Sty_CEL_CML/CML-#1-CP-250ksty.CEL", "Sty_CEL_CML/CML-#10-AP-250ksty.CEL",
> "Sty_CEL_CML/CML-#10-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#11-AP-250ksty.CEL",
> "Sty_CEL_CML/CML-#11-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#12-AP-250ksty.CEL",
> "Sty_CEL_CML/CML-#12-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#12-CP2-250ksty.CEL",
> "Sty_CEL_CML/CML-#13-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#13-CP2-250ksty.CEL",
> "Sty_CEL_CML/CML-#14-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#14-Rem-250ksty.CEL",
> "Sty_CEL_CML/CML-#15-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#15-CP-250ksty.CEL",
> "Sty_CEL_CML/CML-#15-CP2-250ksty.CEL",
"Sty_CEL_CML/CML-#16-BC-250ksty.CEL",
> "Sty_CEL_CML/CML-#16-BC-GL-250ksty.CEL",
> "Sty_CEL_CML/CML-#16-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#16-CP2-250ksty.CEL",
> "Sty_CEL_CML/CML-#17-AP-250ksty.CEL",
"Sty_CEL_CML/CML-#17-CP-250ksty.CEL",
> "Sty_CEL_CML/CML-#18-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#19-BC-250ksty.CEL",
> "Sty_CEL_CML/CML-#19-BC-GL-250ksty.CEL",
> "Sty_CEL_CML/CML-#19-CP-250ksty.CEL", "Sty_CEL_CML/CML-#2-CP-250ksty.CEL",
> "Sty_CEL_CML/CML-#2-CP2-250ksty.CEL",
"Sty_CEL_CML/CML-#20-AP-250ksty.CEL",
> "Sty_CEL_CML/CML-#20-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#20-CP-250ksty.CEL",
> "Sty_CEL_CML/CML-#21-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#21-CP2-250ksty.CEL",
> "Sty_CEL_CML/CML-#22-BC-250ksty.CEL",
> "Sty_CEL_CML/CML-#22-BC-GL-250ksty.CEL",
> "Sty_CEL_CML/CML-#22-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#23-BC-250ksty.CEL",
> "Sty_CEL_CML/CML-#23-BC-GL-250ksty.CEL",
> "Sty_CEL_CML/CML-#23-CP-250ksty.CEL", "Sty_CEL_CML/CML-#3-AP-250ksty.CEL",
> "Sty_CEL_CML/CML-#3-BC-250ksty.CEL", "Sty_CEL_CML/CML-#4-BC-250ksty.CEL",
> "Sty_CEL_CML/CML-#4-CP-250ksty.CEL", "Sty_CEL_CML/CML-#4-Rem-250ksty.CEL",
> "Sty_CEL_CML/CML-#5-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#5-BC-GL-250ksty.CEL",
> "Sty_CEL_CML/CML-#5-Rem-250ksty.CEL", "Sty_CEL_CML/CML-#6-BC-250ksty.CEL",
> "Sty_CEL_CML/CML-#6-BC-GL-250ksty.CEL",
"Sty_CEL_CML/CML-#6-CP-250ksty.CEL",
> "Sty_CEL_CML/CML-#7-BC-250ksty.CEL", "Sty_CEL_CML/CML-#7-CP-250ksty.CEL",
> "Sty_CEL_CML/CML-#8-AP-250ksty.CEL", "Sty_CEL_CML/CML-#8-CP-250ksty.CEL",
> "Sty_CEL_CML/CML-#9-BC-250ksty.CEL",
> "Sty_CEL_CML/CML-#9-BC-GL-250ksty.CEL")[[16L]], ...)
> ?4: lapply(X, FUN, ...)
> ?5: sapply(filenames, function(x) readCelHeader(x)$chiptype)
> ?6: justCRLMMv3(filenames, outdir, batch_size = batch_size, recalibrate =
> recalibrate, ? ? minLLRforCalls = minLLRforCalls, balance = balance,
verbose
> = verbose)
> ?7: crlmm(fullFilenames, outputDir)
>
> Possible actions:
> 1: abort (with core dump, if enabled)
> 2: normal R exit
> 3: exit R without saving workspace
> 4: exit R saving workspace
> Selection:
>
> sessionInfo()
> R version 2.11.1 (2010-05-31)
> x86_64-apple-darwin9.8.0
>
> locale:
> [1] en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8
>
> attached base packages:
> [1] stats ? ? graphics ?grDevices utils ? ? datasets ?methods ? base
>
> other attached packages:
> [1] pd.mapping250k.sty_1.0.0 RSQLite_0.9-2 ? ? ? ? ? ?DBI_0.2-5
> [4] oligo_1.12.2 ? ? ? ? ? ? oligoClasses_1.10.0 ? ? ?Biobase_2.8.0
>
> loaded via a namespace (and not attached):
> [1] affxparser_1.20.0 ? ? affyio_1.16.0 ? ? ? ? Biostrings_2.16.9
> IRanges_1.6.11
> [5] preprocessCore_1.10.0 splines_2.11.1
>
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives:
http://news.gmane.org/gmane.science.biology.informatics.conductor
>
------------------------------
Message: 7
Date: Wed, 15 Sep 2010 11:55:01 -0400
From: "Zhu, Julie" <Julie.Zhu at umassmed.edu>
To: "Benilton Carvalho" <beniltoncarvalho at gmail.com>
Cc: "bioconductor at stat.math.ethz.ch" <bioconductor at stat.math.ethz.ch>
Subject: Re: [BioC] Oligo package crlmm method
Message-ID: <C8B66495.3376%julie.zhu at umassmed.edu>
Content-Type: text/plain; charset=iso-8859-1
Benilton,
Thank you so much for such a quick response!
I tried the following code and got the following error.
Best regards,
Julie
table(sapply(cels, function(x) readCelHeader(x)[["chiptype"]]))
*** caught segfault ***
address 0x1abb9000, cause 'memory not mapped'
Traceback:
1: .Call("R_affx_get_cel_file_header", filename, PACKAGE = "affxparser")
2: readCelHeader(x)
3: FUN(c("Sty_CEL_CML/CML-#1-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#1-CP-250ksty.CEL", "Sty_CEL_CML/CML-#10-AP-250ksty.CEL",
"Sty_CEL_CML/CML-#10-CP-250ksty.CEL", "Sty_CEL_CML/CML-#11-AP-250ksty.CEL",
"Sty_CEL_CML/CML-#11-CP-250ksty.CEL", "Sty_CEL_CML/CML-#12-AP-250ksty.CEL",
"Sty_CEL_CML/CML-#12-CP-250ksty.CEL", "Sty_CEL_CML/CML-#12-CP2-250ksty.CEL",
"Sty_CEL_CML/CML-#13-CP-250ksty.CEL", "Sty_CEL_CML/CML-#13-CP2-250ksty.CEL",
"Sty_CEL_CML/CML-#14-BC-250ksty.CEL", "Sty_CEL_CML/CML-#14-Rem-250ksty.CEL",
"Sty_CEL_CML/CML-#15-BC-250ksty.CEL", "Sty_CEL_CML/CML-#15-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#15-CP2-250ksty.CEL", "Sty_CEL_CML/CML-#16-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#16-BC-GL-250ksty.CEL",
"Sty_CEL_CML/CML-#16-CP-250ksty.CEL", "Sty_CEL_CML/CML-#16-CP2-250ksty.CEL",
"Sty_CEL_CML/CML-#17-AP-250ksty.CEL", "Sty_CEL_CML/CML-#17-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#18-BC-250ksty.CEL", "Sty_CEL_CML/CML-#19-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#19-BC-GL-250ksty.CEL",
"Sty_CEL_CML/CML-#19-CP-250ksty.CEL", "Sty_CEL_CML/CML-#2-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#2-CP2-250ksty.CEL", "Sty_CEL_CML/CML-#20-AP-250ksty.CEL",
"Sty_CEL_CML/CML-#20-BC-250ksty.CEL", "Sty_CEL_CML/CML-#20-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#21-CP-250ksty.CEL", "Sty_CEL_CML/CML-#21-CP2-250ksty.CEL",
"Sty_CEL_CML/CML-#22-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#22-BC-GL-250ksty.CEL",
"Sty_CEL_CML/CML-#22-CP-250ksty.CEL", "Sty_CEL_CML/CML-#23-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#23-BC-GL-250ksty.CEL",
"Sty_CEL_CML/CML-#23-CP-250ksty.CEL", "Sty_CEL_CML/CML-#3-AP-250ksty.CEL",
"Sty_CEL_CML/CML-#3-BC-250ksty.CEL", "Sty_CEL_CML/CML-#4-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#4-CP-250ksty.CEL", "Sty_CEL_CML/CML-#4-Rem-250ksty.CEL",
"Sty_CEL_CML/CML-#5-BC-250ksty.CEL", "Sty_CEL_CML/CML-#5-BC-GL-250ksty.CEL",
"Sty_CEL_CML/CML-#5-Rem-250ksty.CEL", "Sty_CEL_CML/CML-#6-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#6-BC-GL-250ksty.CEL", "Sty_CEL_CML/CML-#6-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#7-BC-250ksty.CEL", "Sty_CEL_CML/CML-#7-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#8-AP-250ksty.CEL", "Sty_CEL_CML/CML-#8-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#9-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#9-BC-GL-250ksty.CEL")[[12L]], ...)
4: lapply(X, FUN, ...)
5: sapply(cels, function(x) readCelHeader(x)[["chiptype"]])
6: table(sapply(cels, function(x) readCelHeader(x)[["chiptype"]]))
Possible actions:
1: abort (with core dump, if enabled)
2: normal R exit
3: exit R without saving workspace
4: exit R saving workspace
Selection:
On 9/15/10 11:43 AM, "Benilton Carvalho" <beniltoncarvalho at gmail.com> wrote:
> Start a new session of R and try the following:
>
> cels = list.files("Sty_CEL_CML", pattern="CEL$", full=TRUE)
> library(affxparser)
> table(sapply(cels, function(x) readCelHeader(x)[["chiptype"]]))
>
> and let me know what you get.
>
> b
>
> On 15 September 2010 16:27, Zhu, Julie <Julie.Zhu at umassmed.edu> wrote:
>> Hi,
>>
>> I am using the crlmm function in Oligo package to make SNP calls. I
>> encountered the following segfault error. Could you please let me know
what
>> could be the cause and how to tackle the problem?
>>
>> Thanks so much for your help!
>>
>> Kind regards,
>>
>> Julie
>>
>> library("oligo")
>> library("pd.mapping250k.sty")
>> fullFilenames <- list.celfiles("Sty_CEL_CML", full.names = TRUE)
>> outputDir <- file.path(getwd(), "crlmmResults_StyCML")
>> if (!file.exists(outputDir)) crlmm(fullFilenames, outputDir)
>>
>> ?*** caught segfault ***
>> address 0x12de80000, cause 'memory not mapped'
>>
>> Traceback:
>> ?1: .Call("R_affx_get_cel_file_header", filename, PACKAGE = "affxparser")
>> ?2: readCelHeader(x)
>> ?3: FUN(c("Sty_CEL_CML/CML-#1-BC-250ksty.CEL",
>> "Sty_CEL_CML/CML-#1-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#10-AP-250ksty.CEL",
>> "Sty_CEL_CML/CML-#10-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#11-AP-250ksty.CEL",
>> "Sty_CEL_CML/CML-#11-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#12-AP-250ksty.CEL",
>> "Sty_CEL_CML/CML-#12-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#12-CP2-250ksty.CEL",
>> "Sty_CEL_CML/CML-#13-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#13-CP2-250ksty.CEL",
>> "Sty_CEL_CML/CML-#14-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#14-Rem-250ksty.CEL",
>> "Sty_CEL_CML/CML-#15-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#15-CP-250ksty.CEL",
>> "Sty_CEL_CML/CML-#15-CP2-250ksty.CEL",
"Sty_CEL_CML/CML-#16-BC-250ksty.CEL",
>> "Sty_CEL_CML/CML-#16-BC-GL-250ksty.CEL",
>> "Sty_CEL_CML/CML-#16-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#16-CP2-250ksty.CEL",
>> "Sty_CEL_CML/CML-#17-AP-250ksty.CEL",
"Sty_CEL_CML/CML-#17-CP-250ksty.CEL",
>> "Sty_CEL_CML/CML-#18-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#19-BC-250ksty.CEL",
>> "Sty_CEL_CML/CML-#19-BC-GL-250ksty.CEL",
>> "Sty_CEL_CML/CML-#19-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#2-CP-250ksty.CEL",
>> "Sty_CEL_CML/CML-#2-CP2-250ksty.CEL",
"Sty_CEL_CML/CML-#20-AP-250ksty.CEL",
>> "Sty_CEL_CML/CML-#20-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#20-CP-250ksty.CEL",
>> "Sty_CEL_CML/CML-#21-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#21-CP2-250ksty.CEL",
>> "Sty_CEL_CML/CML-#22-BC-250ksty.CEL",
>> "Sty_CEL_CML/CML-#22-BC-GL-250ksty.CEL",
>> "Sty_CEL_CML/CML-#22-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#23-BC-250ksty.CEL",
>> "Sty_CEL_CML/CML-#23-BC-GL-250ksty.CEL",
>> "Sty_CEL_CML/CML-#23-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#3-AP-250ksty.CEL",
>> "Sty_CEL_CML/CML-#3-BC-250ksty.CEL", "Sty_CEL_CML/CML-#4-BC-250ksty.CEL",
>> "Sty_CEL_CML/CML-#4-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#4-Rem-250ksty.CEL",
>> "Sty_CEL_CML/CML-#5-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#5-BC-GL-250ksty.CEL",
>> "Sty_CEL_CML/CML-#5-Rem-250ksty.CEL",
"Sty_CEL_CML/CML-#6-BC-250ksty.CEL",
>> "Sty_CEL_CML/CML-#6-BC-GL-250ksty.CEL",
"Sty_CEL_CML/CML-#6-CP-250ksty.CEL",
>> "Sty_CEL_CML/CML-#7-BC-250ksty.CEL", "Sty_CEL_CML/CML-#7-CP-250ksty.CEL",
>> "Sty_CEL_CML/CML-#8-AP-250ksty.CEL", "Sty_CEL_CML/CML-#8-CP-250ksty.CEL",
>> "Sty_CEL_CML/CML-#9-BC-250ksty.CEL",
>> "Sty_CEL_CML/CML-#9-BC-GL-250ksty.CEL")[[16L]], ...)
>> ?4: lapply(X, FUN, ...)
>> ?5: sapply(filenames, function(x) readCelHeader(x)$chiptype)
>> ?6: justCRLMMv3(filenames, outdir, batch_size = batch_size, recalibrate =
>> recalibrate, ? ? minLLRforCalls = minLLRforCalls, balance = balance,
verbose
>> = verbose)
>> ?7: crlmm(fullFilenames, outputDir)
>>
>> Possible actions:
>> 1: abort (with core dump, if enabled)
>> 2: normal R exit
>> 3: exit R without saving workspace
>> 4: exit R saving workspace
>> Selection:
>>
>> sessionInfo()
>> R version 2.11.1 (2010-05-31)
>> x86_64-apple-darwin9.8.0
>>
>> locale:
>> [1] en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8
>>
>> attached base packages:
>> [1] stats ? ? graphics ?grDevices utils ? ? datasets ?methods ? base
>>
>> other attached packages:
>> [1] pd.mapping250k.sty_1.0.0 RSQLite_0.9-2 ? ? ? ? ? ?DBI_0.2-5
>> [4] oligo_1.12.2 ? ? ? ? ? ? oligoClasses_1.10.0 ? ? ?Biobase_2.8.0
>>
>> loaded via a namespace (and not attached):
>> [1] affxparser_1.20.0 ? ? affyio_1.16.0 ? ? ? ? Biostrings_2.16.9
>> IRanges_1.6.11
>> [5] preprocessCore_1.10.0 splines_2.11.1
>>
>> _______________________________________________
>> Bioconductor mailing list
>> Bioconductor at stat.math.ethz.ch
>> https://stat.ethz.ch/mailman/listinfo/bioconductor
>> Search the archives:
>> http://news.gmane.org/gmane.science.biology.informatics.conductor
>>
>
------------------------------
Message: 8
Date: Wed, 15 Sep 2010 12:03:48 -0400
From: Sean Davis <sdavis2 at mail.nih.gov>
To: Yogesh <yogeshp08 at gmail.com>
Cc: Bioconductor-R Mailing List <bioconductor at stat.math.ethz.ch>
Subject: Re: [BioC] Comparing 2 GEO datasets
Message-ID:
<AANLkTik8P=ZN094qDDEy+HQzfWvEQWMYUsbF2g5kBjdp at mail.gmail.com>
Content-Type: text/plain
On Wed, Sep 15, 2010 at 10:48 AM, Yogesh <yogeshp08 at gmail.com> wrote:
> Hello,
>
> I want to compare two GEO datasets based on the time series data. I want
to
> be able to draw some visual highlighting/showing the difference in the
> expression of the two sets.
>
> Can some one please guide me on how to go about it?
>
>
Hi, Yogesh.
It is not really possible to answer this question as your problem is much
too vague. You will need to be much more detailed about what you are
planning and what you have already done.
Sean
[[alternative HTML version deleted]]
------------------------------
Message: 9
Date: Wed, 15 Sep 2010 12:36:01 -0400
From: Yogesh <yogeshp08 at gmail.com>
To: Sean Davis <sdavis2 at mail.nih.gov>
Cc: Bioconductor-R Mailing List <bioconductor at stat.math.ethz.ch>
Subject: Re: [BioC] Comparing 2 GEO datasets
Message-ID:
<AANLkTikyF0nikv_Y4oN_iPHGsh04VG3SzrUZ3szDK=ga at mail.gmail.com>
Content-Type: text/plain
Hi Sean,
I have two GEO sets to compare (from two different experiments). I tried to
use limma package. But most of the packages use groups within a single
dataset for the t-test. I have 2 datasets with 24 time-points each. The
basic experiment in both cases is the same. I want to compare, say
time-point 0min vs. time-point 0min from both sets. I do not know what the
expression is. I want to check if the expression changes at a particular
time-point (from 0-24 time-points). I believe a line-chart or a volcano-plot
(single time-point or whole set) will help understand this better.
I thought I will ask for some guidance on how to go about it so that I can
try something in that direction.
Thanks,
-Yogesh
On 15 September 2010 12:03, Sean Davis <sdavis2 at mail.nih.gov> wrote:
>
> On Wed, Sep 15, 2010 at 10:48 AM, Yogesh <yogeshp08 at gmail.com> wrote:
>
>> Hello,
>>
>> I want to compare two GEO datasets based on the time series data. I want
>> to
>> be able to draw some visual highlighting/showing the difference in the
>> expression of the two sets.
>>
>> Can some one please guide me on how to go about it?
>>
>>
> Hi, Yogesh.
>
> It is not really possible to answer this question as your problem is much
> too vague. You will need to be much more detailed about what you are
> planning and what you have already done.
>
> Sean
>
>
[[alternative HTML version deleted]]
------------------------------
Message: 10
Date: Wed, 15 Sep 2010 12:46:20 -0400
From: "Zhu, Julie" <Julie.Zhu at umassmed.edu>
To: "Benilton Carvalho" <beniltoncarvalho at gmail.com>
Cc: "bioconductor at stat.math.ethz.ch" <bioconductor at stat.math.ethz.ch>
Subject: Re: [BioC] Oligo package crlmm method
Message-ID: <C8B6709C.337F%julie.zhu at umassmed.edu>
Content-Type: text/plain; charset=iso-8859-1
Benilton,
Thanks for the debugging code! It helped me to get down to two files with
unreadable header.
Best regards,
Julie
On 9/15/10 11:55 AM, "Julie Zhu" <julie.zhu at umassmed.edu> wrote:
> Benilton,
>
> Thank you so much for such a quick response!
>
> I tried the following code and got the following error.
>
> Best regards,
>
> Julie
>
>
> table(sapply(cels, function(x) readCelHeader(x)[["chiptype"]]))
>
> *** caught segfault ***
> address 0x1abb9000, cause 'memory not mapped'
>
> Traceback:
> 1: .Call("R_affx_get_cel_file_header", filename, PACKAGE = "affxparser")
> 2: readCelHeader(x)
> 3: FUN(c("Sty_CEL_CML/CML-#1-BC-250ksty.CEL",
> "Sty_CEL_CML/CML-#1-CP-250ksty.CEL", "Sty_CEL_CML/CML-#10-AP-250ksty.CEL",
> "Sty_CEL_CML/CML-#10-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#11-AP-250ksty.CEL",
> "Sty_CEL_CML/CML-#11-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#12-AP-250ksty.CEL",
> "Sty_CEL_CML/CML-#12-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#12-CP2-250ksty.CEL",
> "Sty_CEL_CML/CML-#13-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#13-CP2-250ksty.CEL",
> "Sty_CEL_CML/CML-#14-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#14-Rem-250ksty.CEL",
> "Sty_CEL_CML/CML-#15-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#15-CP-250ksty.CEL",
> "Sty_CEL_CML/CML-#15-CP2-250ksty.CEL",
"Sty_CEL_CML/CML-#16-BC-250ksty.CEL",
> "Sty_CEL_CML/CML-#16-BC-GL-250ksty.CEL",
> "Sty_CEL_CML/CML-#16-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#16-CP2-250ksty.CEL",
> "Sty_CEL_CML/CML-#17-AP-250ksty.CEL",
"Sty_CEL_CML/CML-#17-CP-250ksty.CEL",
> "Sty_CEL_CML/CML-#18-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#19-BC-250ksty.CEL",
> "Sty_CEL_CML/CML-#19-BC-GL-250ksty.CEL",
> "Sty_CEL_CML/CML-#19-CP-250ksty.CEL", "Sty_CEL_CML/CML-#2-CP-250ksty.CEL",
> "Sty_CEL_CML/CML-#2-CP2-250ksty.CEL",
"Sty_CEL_CML/CML-#20-AP-250ksty.CEL",
> "Sty_CEL_CML/CML-#20-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#20-CP-250ksty.CEL",
> "Sty_CEL_CML/CML-#21-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#21-CP2-250ksty.CEL",
> "Sty_CEL_CML/CML-#22-BC-250ksty.CEL",
> "Sty_CEL_CML/CML-#22-BC-GL-250ksty.CEL",
> "Sty_CEL_CML/CML-#22-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#23-BC-250ksty.CEL",
> "Sty_CEL_CML/CML-#23-BC-GL-250ksty.CEL",
> "Sty_CEL_CML/CML-#23-CP-250ksty.CEL", "Sty_CEL_CML/CML-#3-AP-250ksty.CEL",
> "Sty_CEL_CML/CML-#3-BC-250ksty.CEL", "Sty_CEL_CML/CML-#4-BC-250ksty.CEL",
> "Sty_CEL_CML/CML-#4-CP-250ksty.CEL", "Sty_CEL_CML/CML-#4-Rem-250ksty.CEL",
> "Sty_CEL_CML/CML-#5-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#5-BC-GL-250ksty.CEL",
> "Sty_CEL_CML/CML-#5-Rem-250ksty.CEL", "Sty_CEL_CML/CML-#6-BC-250ksty.CEL",
> "Sty_CEL_CML/CML-#6-BC-GL-250ksty.CEL",
"Sty_CEL_CML/CML-#6-CP-250ksty.CEL",
> "Sty_CEL_CML/CML-#7-BC-250ksty.CEL", "Sty_CEL_CML/CML-#7-CP-250ksty.CEL",
> "Sty_CEL_CML/CML-#8-AP-250ksty.CEL", "Sty_CEL_CML/CML-#8-CP-250ksty.CEL",
> "Sty_CEL_CML/CML-#9-BC-250ksty.CEL",
> "Sty_CEL_CML/CML-#9-BC-GL-250ksty.CEL")[[12L]], ...)
> 4: lapply(X, FUN, ...)
> 5: sapply(cels, function(x) readCelHeader(x)[["chiptype"]])
> 6: table(sapply(cels, function(x) readCelHeader(x)[["chiptype"]]))
>
> Possible actions:
> 1: abort (with core dump, if enabled)
> 2: normal R exit
> 3: exit R without saving workspace
> 4: exit R saving workspace
> Selection:
>
>
> On 9/15/10 11:43 AM, "Benilton Carvalho" <beniltoncarvalho at gmail.com>
wrote:
>
>> Start a new session of R and try the following:
>>
>> cels = list.files("Sty_CEL_CML", pattern="CEL$", full=TRUE)
>> library(affxparser)
>> table(sapply(cels, function(x) readCelHeader(x)[["chiptype"]]))
>>
>> and let me know what you get.
>>
>> b
>>
>> On 15 September 2010 16:27, Zhu, Julie <Julie.Zhu at umassmed.edu> wrote:
>>> Hi,
>>>
>>> I am using the crlmm function in Oligo package to make SNP calls. I
>>> encountered the following segfault error. Could you please let me know
what
>>> could be the cause and how to tackle the problem?
>>>
>>> Thanks so much for your help!
>>>
>>> Kind regards,
>>>
>>> Julie
>>>
>>> library("oligo")
>>> library("pd.mapping250k.sty")
>>> fullFilenames <- list.celfiles("Sty_CEL_CML", full.names = TRUE)
>>> outputDir <- file.path(getwd(), "crlmmResults_StyCML")
>>> if (!file.exists(outputDir)) crlmm(fullFilenames, outputDir)
>>>
>>> ?*** caught segfault ***
>>> address 0x12de80000, cause 'memory not mapped'
>>>
>>> Traceback:
>>> ?1: .Call("R_affx_get_cel_file_header", filename, PACKAGE =
"affxparser")
>>> ?2: readCelHeader(x)
>>> ?3: FUN(c("Sty_CEL_CML/CML-#1-BC-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#1-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#10-AP-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#10-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#11-AP-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#11-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#12-AP-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#12-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#12-CP2-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#13-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#13-CP2-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#14-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#14-Rem-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#15-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#15-CP-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#15-CP2-250ksty.CEL",
"Sty_CEL_CML/CML-#16-BC-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#16-BC-GL-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#16-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#16-CP2-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#17-AP-250ksty.CEL",
"Sty_CEL_CML/CML-#17-CP-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#18-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#19-BC-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#19-BC-GL-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#19-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#2-CP-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#2-CP2-250ksty.CEL",
"Sty_CEL_CML/CML-#20-AP-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#20-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#20-CP-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#21-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#21-CP2-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#22-BC-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#22-BC-GL-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#22-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#23-BC-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#23-BC-GL-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#23-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#3-AP-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#3-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#4-BC-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#4-CP-250ksty.CEL",
"Sty_CEL_CML/CML-#4-Rem-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#5-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#5-BC-GL-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#5-Rem-250ksty.CEL",
"Sty_CEL_CML/CML-#6-BC-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#6-BC-GL-250ksty.CEL",
"Sty_CEL_CML/CML-#6-CP-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#7-BC-250ksty.CEL",
"Sty_CEL_CML/CML-#7-CP-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#8-AP-250ksty.CEL",
"Sty_CEL_CML/CML-#8-CP-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#9-BC-250ksty.CEL",
>>> "Sty_CEL_CML/CML-#9-BC-GL-250ksty.CEL")[[16L]], ...)
>>> ?4: lapply(X, FUN, ...)
>>> ?5: sapply(filenames, function(x) readCelHeader(x)$chiptype)
>>> ?6: justCRLMMv3(filenames, outdir, batch_size = batch_size, recalibrate
=
>>> recalibrate, ? ? minLLRforCalls = minLLRforCalls, balance = balance,
verbose
>>> = verbose)
>>> ?7: crlmm(fullFilenames, outputDir)
>>>
>>> Possible actions:
>>> 1: abort (with core dump, if enabled)
>>> 2: normal R exit
>>> 3: exit R without saving workspace
>>> 4: exit R saving workspace
>>> Selection:
>>>
>>> sessionInfo()
>>> R version 2.11.1 (2010-05-31)
>>> x86_64-apple-darwin9.8.0
>>>
>>> locale:
>>> [1] en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8
>>>
>>> attached base packages:
>>> [1] stats ? ? graphics ?grDevices utils ? ? datasets ?methods ? base
>>>
>>> other attached packages:
>>> [1] pd.mapping250k.sty_1.0.0 RSQLite_0.9-2 ? ? ? ? ? ?DBI_0.2-5
>>> [4] oligo_1.12.2 ? ? ? ? ? ? oligoClasses_1.10.0 ? ? ?Biobase_2.8.0
>>>
>>> loaded via a namespace (and not attached):
>>> [1] affxparser_1.20.0 ? ? affyio_1.16.0 ? ? ? ? Biostrings_2.16.9
>>> IRanges_1.6.11
>>> [5] preprocessCore_1.10.0 splines_2.11.1
>>>
>>> _______________________________________________
>>> Bioconductor mailing list
>>> Bioconductor at stat.math.ethz.ch
>>> https://stat.ethz.ch/mailman/listinfo/bioconductor
>>> Search the archives:
>>> http://news.gmane.org/gmane.science.biology.informatics.conductor
>>>
>>
>
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives:
> http://news.gmane.org/gmane.science.biology.informatics.conductor
>
------------------------------
Message: 11
Date: Wed, 15 Sep 2010 10:48:33 -0600
From: "Brown, Joseph" <BrownJo at NJHealth.org>
To: bioconductor at stat.math.ethz.ch
Subject: Re: [BioC] Agi4x44PreProcess- RSQLite driver:
(RS_SQLite_fetch: failed first step: disk I/O error)
Message-ID:
<24B2F1E784B3A8498804477290B70C4003718B87 at ePostoffice.NJRC.ORG>
Content-Type: text/plain
Regarding: RSQLite driver: (RS_SQLite_fetch: failed first step: disk I/O
error)
We successfully diagnosed and solved this problem. We tried the
suggestions of installing the R packages on a local disk and ran
RSQLite-specific commands which indicated the RSQLite-package was
installed
and working but the error persisted. The problem manifested in a call
to the lookUp() function of the 'annotate' package which uses
RSQLite. It appeared that for the version installed on the server,
there was some hard-coded limit in the underlying (non-R) SQLite that
caused calls to lookUp() with > 24814 items to throw the error.
In particular, sqlite 3.3.6-2 was installed on our server that
demonstrated the error, while on a separate server running 3.3.6-5,
the function ran properly. Thus, we installed sqlite with the newest
date on the src tree under 3.3.6 from
http://www.sqlite.org/src/info/715cecb8c7 on our server and we no
longer see this error.
For future reference, this snippet of code was enough to pinpoint the
problem (we noticed that could use lookUp for subsets of all PROBE_ID
but
not for the full vector of PROBE_ID):
-----------------------
library(annotate)
library(mgug4112a.db)
PROBE_ID = <list of probe ids>
# This returns ACCNUM without error for first PROBE_ID
GENE_ID= lookUp(PROBE_ID[1], 'mgug4112a.db', "ACCNUM")
# This gets RSQLite error and any subsequent calls to lookUp show
# error, have to restart R session to reset -> dislikes whole vector as
input
GENE_ID= lookUp(PROBE_ID, 'mgug4112a.db', "ACCNUM") # has RSQLite error
# This displays ACCNUM for each PROBE_ID individually, without error
# so problem isn't a specific PROBE_ID[i]
for (i in 0:length(PROBE_ID)) {
GENE_ID= lookUp(PROBE_ID[i], 'mgug4112a.db', "ACCNUM");
cat(i, " ", GENE_ID,"\n")
}
# This displays i-th ACCNUM when lookUp 1:i but get error for
# i=24815, reproducibly and any subsequent call to lookUp displays
# RSQLite error - seems to be hard-coded size limit in SQLite
for (i in 0:length(PROBE_ID)) {
GENE_ID= lookUp(PROBE_ID[1:i], 'mgug4112a.db', "ACCNUM");
cat(i, " ", GENE_ID[i],"\n")
}
--------- Previous Posts -----------------------------
From: Benilton Carvalho [mailto:beniltoncarvalho at gmail.com]
Sent: Wednesday, August 25, 2010 2:44 PM
To: Brown, Joseph
Cc: bioconductor at stat.math.ethz.ch
Subject: Re: [BioC] Agi4x44PreProcess- RSQLite driver: (RS_SQLite_fetch:
failed first step: disk I/O error)
I have seen something similar (with RSQLite alone)... and, back in the
day, it appeared to have an association with the fact that the library
directory was on a network drive (and the connection of the machine
with the storage system was not that great)...
Installing the RSQLite-dependent package on a local disk always solved
the problem for me...
b
On 25 August 2010 21:10, Brown, Joseph <BrownJo at njhealth.org> wrote:
> Issue:
>
> When trying to execute filter.probes the following error occurs:
>
>>ddFILT=filter.probes(ddNORM,control,wellaboveBG,isfound,wellaboveNEG,s
a
>
t,PopnOL,NonUnifOL,nas,limWellAbove,limISF,limNEG,limSAT,limPopnOL,limNo
> nUnifOL,limNAS,makePLOT=FALSE, annotation.package,flag.counts,targets)
>
> FILTERING PROBES BY FLAGS
>
>
>
>
>
> FILTERING BY ControlType FLAG
>
> Error in sqliteFetch(rs, n = -1, ...) :
>
> RSQLite driver: (RS_SQLite_fetch: failed first step: disk I/O error)
>
>
>
>
>
> This issue is reproducible on this particular Linux installation only
> (craps out on all data sets, including sets known to work), so I've
> tried uninstalling and reinstalling R, as well as the packages,
several
> times. Utilizing the same data, I have been able to get results using
> Windows installations and other Linux installs.
>
>
>
> Has anyone seen this error before and/or have ideas to remedy the
> problem?
>
>
>
> My session info:
>
>> sessionInfo()
>
> R version 2.11.1 (2010-05-31)
>
> x86_64-unknown-linux-gnu
>
>
>
> locale:
>
> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
>
> [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
>
> [5] LC_MONETARY=C LC_MESSAGES=en_US.UTF-8
>
> [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
>
> [9] LC_ADDRESS=C LC_TELEPHONE=C
>
> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
>
>
>
> attached base packages:
>
> [1] stats graphics grDevices utils datasets methods base
>
>
>
> other attached packages:
>
> [1] vsn_3.16.0 mgug4122a.db_2.4.1
org.Mm.eg.db_2.4.1
>
> [4] RSQLite_0.9-2 DBI_0.2-5
> Agi4x44PreProcess_1.8.0
>
> [7] genefilter_1.30.0 annotate_1.26.1
> AnnotationDbi_1.10.2
>
> [10] limma_3.4.4 Biobase_2.8.0
>
>
>
> loaded via a namespace (and not attached):
>
> [1] affy_1.26.1 affyio_1.16.0 grid_2.11.1
>
> [4] lattice_0.18-8 preprocessCore_1.10.0 splines_2.11.1
>
> [7] survival_2.35-8 xtable_1.5-6
>
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------------------------------
Message: 12
Date: Wed, 15 Sep 2010 12:49:29 -0400
From: Sean Davis <sdavis2 at mail.nih.gov>
To: Yogesh <yogeshp08 at gmail.com>
Cc: Bioconductor-R Mailing List <bioconductor at stat.math.ethz.ch>
Subject: Re: [BioC] Comparing 2 GEO datasets
Message-ID:
<AANLkTi=r7Mk8Ag2rb+HqsSMRHwj4k2Gkms8_6q8-_Vp_ at mail.gmail.com>
Content-Type: text/plain
On Wed, Sep 15, 2010 at 12:36 PM, Yogesh <yogeshp08 at gmail.com> wrote:
> Hi Sean,
>
> I have two GEO sets to compare (from two different experiments). I tried
to
> use limma package. But most of the packages use groups within a single
> dataset for the t-test. I have 2 datasets with 24 time-points each. The
> basic experiment in both cases is the same. I want to compare, say
> time-point 0min vs. time-point 0min from both sets. I do not know what the
> expression is. I want to check if the expression changes at a particular
> time-point (from 0-24 time-points). I believe a line-chart or a
volcano-plot
> (single time-point or whole set) will help understand this better.
>
>
You will not likely be able to compare the two datasets to each other using
a t-test or any other test, for that matter, given the perfect confounding
of experimental effect and lab/technical variation between the two datasets.
Perhaps I am misunderstanding what you are trying to do, though.
Sean
> I thought I will ask for some guidance on how to go about it so that I can
> try something in that direction.
>
> Thanks,
>
> -Yogesh
>
>
>
> On 15 September 2010 12:03, Sean Davis <sdavis2 at mail.nih.gov> wrote:
>
>>
>> On Wed, Sep 15, 2010 at 10:48 AM, Yogesh <yogeshp08 at gmail.com> wrote:
>>
>>> Hello,
>>>
>>> I want to compare two GEO datasets based on the time series data. I want
>>> to
>>> be able to draw some visual highlighting/showing the difference in the
>>> expression of the two sets.
>>>
>>> Can some one please guide me on how to go about it?
>>>
>>>
>> Hi, Yogesh.
>>
>> It is not really possible to answer this question as your problem is much
>> too vague. You will need to be much more detailed about what you are
>> planning and what you have already done.
>>
>> Sean
>>
>>
>
>
[[alternative HTML version deleted]]
------------------------------
Message: 13
Date: Wed, 15 Sep 2010 13:12:19 -0400
From: Yogesh <yogeshp08 at gmail.com>
To: Sean Davis <sdavis2 at mail.nih.gov>
Cc: Bioconductor-R Mailing List <bioconductor at stat.math.ethz.ch>
Subject: Re: [BioC] Comparing 2 GEO datasets
Message-ID:
<AANLkTinMo-6ASk_AtUkVpXwSRshW2qXua8bKW9RgFpJz at mail.gmail.com>
Content-Type: text/plain
Hi Sean,
You are right. I agree. Biologically, it may not be possible to compare
because of the experimental conditions. But can it be done just
statistically.
-Yogesh
On 15 September 2010 12:49, Sean Davis <sdavis2 at mail.nih.gov> wrote:
>
>
> On Wed, Sep 15, 2010 at 12:36 PM, Yogesh <yogeshp08 at gmail.com> wrote:
>
>> Hi Sean,
>>
>> I have two GEO sets to compare (from two different experiments). I tried
>> to use limma package. But most of the packages use groups within a single
>> dataset for the t-test. I have 2 datasets with 24 time-points each. The
>> basic experiment in both cases is the same. I want to compare, say
>> time-point 0min vs. time-point 0min from both sets. I do not know what
>> the expression is. I want to check if the expression changes at a
particular
>> time-point (from 0-24 time-points). I believe a line-chart or a
volcano-plot
>> (single time-point or whole set) will help understand this better.
>>
>>
> You will not likely be able to compare the two datasets to each other
using
> a t-test or any other test, for that matter, given the perfect confounding
> of experimental effect and lab/technical variation between the two
datasets.
> Perhaps I am misunderstanding what you are trying to do, though.
>
> Sean
>
[[alternative HTML version deleted]]
------------------------------
Message: 14
Date: Tue, 14 Sep 2010 13:36:51 -0400
From: sohkhan at notes.cc.sunysb.edu
To: Wolfgang Huber <whuber at embl.de>
Cc: bioconductor-bounces at stat.math.ethz.ch,
bioconductor at stat.math.ethz.ch
Subject: Re: [BioC] probeAnno for tilingArray package.
Message-ID:
<OF58C99901.2A658DA7-ON8525779E.005FD5D3-8525779E.0060C3C2 at notes.cc.sunysb.e
du>
Content-Type: text/plain
Thank you Wolfgang.
I corrected the chr parameter as suggested by Noah. segChrom runs with
strand=NA. Now, I have question about the probeAnno creation by
bpmapToProbeAnno(). Does the function treat 0's as "-" and 1's "+" strand.
I have just one BPMAP file for S.pombe from Affymetrix which contains 0's
and 1's in the strand column.
Thanks again.
-Sohail
From: Wolfgang Huber <whuber at embl.de>
To: bioconductor at stat.math.ethz.ch
Date: 09/11/2010 08:15 AM
Subject: Re: [BioC] probeAnno for tilingArray package.
Sent by: bioconductor-bounces at stat.math.ethz.ch
Dear Sohail
in R, the character string "NA" is different from the value NA. Try with
supplying the second one for the argument 'strands'. Also, please make
sure that the 'chr' argument is set to the right value, the default
(1:17) is likely not to work with S.pombe. You can see what the
chromosome names are in your organism by inspecting the probeAnno object.
Best wishes
Wolfgang
On Sep/8/10 10:33 PM, sohkhan at notes.cc.sunysb.edu wrote:
> Hi all,
>
> I am trying to use the "tilingArray" package to analyze Affymetrix
S.pombe
> tiling arrays. I downloaded the .bpmap file from Affymetrix's website,
> and created a probeAnno object by bpmapToProbeAnno().
> However, I am getting the following error when I try to segment the data
> by segChrom().
>
>> segdf<-segChrom(cels,probeAnno,strands="NA")
> Running 'segment' on chromosome 1.NAError in probeAnno[w] :
> No mapping '1.NA.start' in this 'probeAnno' object.
>
>> sessionInfo()
> R version 2.11.1 (2010-05-31)
> x86_64-apple-darwin9.8.0
>
> locale:
> [1] en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8
>
> attached base packages:
> [1] grid stats graphics grDevices utils datasets methods
> base
>
> other attached packages:
> [1] davidTiling_1.2.12 GO.db_2.4.1 RSQLite_0.9-2 DBI_0.2-5
> AnnotationDbi_1.10.2 tilingArray_1.26.0 pixmap_0.4-10 Starr_1.4.4
>
> [9] affy_1.26.1 Ringo_1.12.0 Matrix_0.999375-39
> lattice_0.18-8 limma_3.4.4 RColorBrewer_1.0-2
Biobase_2.8.0
> affxparser_1.20.0
>
> loaded via a namespace (and not attached):
> [1] affyio_1.16.0 annotate_1.26.1 genefilter_1.30.0
> MASS_7.3-6 preprocessCore_1.10.0 pspline_1.0-14
splines_2.11.1
> strucchange_1.4-1
> [9] survival_2.35-8 tools_2.11.1 vsn_3.16.0
xtable_1.5-6
>
>
> I am wondering if I used the correct .bpmap file??
> Thanks for any suggestion/advice.
>
> -Sohail
> SBU, NY
>>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives:
http://news.gmane.org/gmane.science.biology.informatics.conductor
--
Wolfgang Huber
EMBL
http://www.embl.de/research/units/genome_biology/huber
_______________________________________________
Bioconductor mailing list
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Search the archives:
http://news.gmane.org/gmane.science.biology.informatics.conductor
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------------------------------
Message: 15
Date: Wed, 15 Sep 2010 12:59:19 +0100
From: Elizabeth Ashley <elizabeth.ashley at linacre.ox.ac.uk>
To: "bioconductor at stat.math.ethz.ch" <bioconductor at stat.math.ethz.ch>
Subject: [BioC] Querying clustering in heatmap.2
Message-ID:
<01B4B1C924D5FC44B57B269548B562763C553B8634 at EXMBX05.ad.oak.ox.ac.uk>
Content-Type: text/plain; charset="us-ascii"
Hi
I have used heatmap.2 to create a heatmap of my data. It automatically
clusters the data and I can't identify which part of the text does this.
However I am quite happy to have the clustering (of GO categories) but would
like to be able to query the groupings to find insights into how it is
clustered. Are these clusters named, and if so can you find out which ones
bring back significant data? Below is the script I am using.
GO<-read.delim("file.txt",header=TRUE)
GO
GO[,-c(1)]
row.names(GO)<-GO$NAMES
source("http://www.bioconductor.org/biocLite.R")
biocLite("ALL")
library("Ringo")
GO_matrix<-data.matrix(GO[,-c(1)])
source("http://www.bioconductor.org/biocLite.R")
biocLite("limma")
library(limma)
library(gplots)
heatmap.2(GO_matrix,col=redgreen(256),
margins=c(5,10),xlab="DATASET",ylab="GO TERM",
key=TRUE,keysize=1,symkey=FALSE,density.info="none",
trace="none",cexCol=0.5,cexRow=0.1)
Thanks for any help you can provide with this matter
Lizzy
------------------------------
Message: 16
Date: Wed, 15 Sep 2010 19:35:02 +0200
From: Eva Benito Garagorri <ebenito at umh.es>
To: bioconductor at stat.math.ethz.ch
Subject: [BioC] BioNet - interpretation of node score
Message-ID: <2EE8CB0B-170D-42B1-9625-6BB9F128D66F at umh.es>
Content-Type: text/plain
Dear List,
I have recently started exploring the Package BioNet for network analysis
of microarray data. I have a fundamental question about the interpretation
of the results. From my understanding, BioNet first takes a series of
p-values, fits them to a model, and then uses this information to score the
nodes of a given network (the package is based on a human protein-protein
interaction network) and output the best scoring subnetwork. In the 2D
visualization of this subnetwork, squares represent nodes with a negative
score and circles represent nodes with a positive score. What I do not
understand is what the sign of the scores represents, i.e., what is the
interpretation of an interaction between two positive nodes vs the
interaction of two negative nodes?
I am attaching the code from the BioNet Tutorial for the introductory
example, only I am not aggregating the pvalues, but rather just taking the
pvalues for differential expression (because I am only using this
information for my own data). I also changed the FDR threshold so that the
resulting network would be smaller.
Thanks a lot in advance.
Best,
Eva
----------
Eva Benito Garagorri
PhD program in Neurosciences
Institute for Neurosciences in Alicante
UMH-CSIC
San Juan de Alicante
03550
Spain
ebenito at umh.es
(34) 965 91 92 33
----------------
library(BioNet)
library(DLBCL)
data(dataLym)
data(interactome)
pvals=dataLym$t.pval
names(pvals)=dataLym$label
subnet=subNetwork(dataLym$label,interactome)
subnet=rmSelfLoops(subnet)
fb=fitBumModel(pvals,plot=FALSE)
scores=scoreNodes(subnet,fb,fdr=0.000001)
module=runFastHeinz(subnet,scores)
logFC=dataLym$diff
names(logFC)=dataLym$label
plotModule(module,scores=scores,diff.expr=logFC)
----------
> sessionInfo()
R version 2.11.1 (2010-05-31)
x86_64-apple-darwin9.8.0
locale:
[1] es_ES.UTF-8/es_ES.UTF-8/C/C/es_ES.UTF-8/es_ES.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] DLBCL_1.2 BioNet_1.6.5 RBGL_1.24.0 graph_1.26.0 Biobase_2.8.0
loaded via a namespace (and not attached):
[1] AnnotationDbi_1.10.2 DBI_0.2-5 igraph_0.5.4
[4] RSQLite_0.9-2 tools_2.11.1 XML_3.1-0
>
[[alternative HTML version deleted]]
------------------------------
Message: 17
Date: Wed, 15 Sep 2010 11:52:10 -0700
From: Josef Spidlen <jspidlen at bccrc.ca>
To: Roger Leigh <rleigh at codelibre.net>
Cc: "bioconductor at stat.math.ethz.ch" <bioconductor at stat.math.ethz.ch>
Subject: Re: [BioC] Gating with an ellipsoidGate
Message-ID: <4C9115DA.2080506 at bccrc.ca>
Content-Type: text/plain; charset="ISO-8859-1"; format=flowed
Hi Roger,
your calculation of the covariance matrix seems fine to me.
All seems working fine if your data is on linear axis. I tried the
following:
library(flowCore)
library(flowViz)
x <- read.FCS('A01.fcs')
cov <- cov.matrix(150, 50, 45)
mean <- c(200, 100)
names(mean) <- colnames(x)[1:2]
colnames(cov) <- colnames(x)[1:2]
rownames(cov) <- colnames(x)[1:2]
cells <- ellipsoidGate(filterId="CellGate", .gate=cov, mean=mean)
xyplot(`FSC-H` ~ `SSC-H`, x, filter=cells)
where the data file can be downloaded from
http://flowcyt.sf.net/temp/A01.fcs
and cov.matrix is from your code, namely:
cov.matrix <- function (a, b, angle) {
theta <- angle * (pi/180)
c1 <- ((cos(theta)^2)/a^2) + ((sin(theta)^2)/b^2)
c2 <- sin(theta) * cos(theta) * ((1/a^2) - (1/b^2))
c3 <- ((sin(theta)^2)/a^2) + ((cos(theta)^2)/b^2)
m1 <- matrix(c(c1, c2, c2, c3), byrow=TRUE, ncol=2)
m2 <- solve(m1)
m2
}
This is working well for different angles and - by-eye - the rotation of
the ellipse corresponds to the one requested.
I am thinking whether your issue is a bug in flowCore/flowViz or just an
artifact of having completely different scales for x and y. What I mean
is that your ellipse is essentially 50,000x longer in the x dimension
than in y dimension and flowViz "adjusts" for that in the display -
scaling x and y completely different. If you rotate it even only a tiny
bit, everything changes drastically and the new ellipse now needs a
completely different scales to show up reasonably.
My feeling is that rotating an ellipse in a space that consist of one
linear and one log dimension may not be very meaningful and may create
weird artifacts. Could you maybe scale the data somehow so that x/y get
on similar value range and try if that would work
Cheers,
Josef
On 10-09-15 04:37 AM, Roger Leigh wrote:
> On 15/09/2010 12:24, Roger Leigh wrote:
>
>> This appears to work well when rotation is not involved. However, as
>> soon as I try to add rotation, it blows up:
>>
>> library(flowCore)
>> library(flowViz)
>> library(flowUtils)
>>
>> cov.matrix<- function (a, b, angle) {
>> theta<- angle * (pi/180)
>>
>> c1<- ((cos(theta)^2)/a^2) + ((sin(theta)^2)/b^2)
>> c2<- sin(theta) * cos(theta) * ((1/a^2) - (1/b^2))
>> c3<- ((sin(theta)^2)/a^2) + ((cos(theta)^2)/b^2)
>>
>> m1<- matrix(c(c1, c2, c2, c3), byrow=TRUE, ncol=2)
>> m2<- solve(m1)
>>
>> m2
>> }
>>
>> d<- read.FCS("0isotype.fcs", alter.names=TRUE)
>> d<- transform(d, `SS.Log` = log10(`SS.Log`))
>>
>> # No rotation
>> cov<- cov.matrix(20000, 0.4, 0)
>> colnames(cov)<- c("FS.Lin", "SS.Log")
>> rownames(cov)<- c("FS.Lin", "SS.Log")
>> mean<- c("FS.Lin"=40000, "SS.Log"=2.8)
>> cells<- ellipsoidGate(filterId="CellGate", .gate=cov, mean=mean)
>> print(cov)
>> pdf("test.pdf", width=8, height=8, pointsize=12)
>> print(xyplot(`SS.Log` ~ `FS.Lin`, d, filter=cells, xlab="FS",
>> ylab=expression(log[10]~(SS))))
>> dev.off()
>>
>> # Now repeat with a 20 degree rotation...
>> cov<- cov.matrix(20000, 0.4, 20)
>> colnames(cov)<- c("FS.Lin", "SS.Log")
>> rownames(cov)<- c("FS.Lin", "SS.Log")
>> mean<- c("FS.Lin"=40000, "SS.Log"=2.8)
>> cells<- ellipsoidGate(filterId="CellGate", .gate=cov, mean=mean)
>> print(cov)
>>
>> pdf("test-rotate.pdf", width=8, height=8, pointsize=12)
>> print(xyplot(`SS.Log` ~ `FS.Lin`, d, filter=cells, xlab="FS",
>> ylab=expression(log[10]~(SS))))
>> dev.off()
>>
>> I've put the source data, script and results at:
>> http://www-users.york.ac.uk/~rl522/flowcore-test/
>>
>> http://www-users.york.ac.uk/~rl522/flowcore-test/test.pdf
>> http://www-users.york.ac.uk/~rl522/flowcore-test/test-rotate.pdf
>>
>> You can see that while an ellipse is drawn correctly in the first
>> instance, when we add a 20 degree rotation, it's completely screwed. I'm
>> not sure if this is due to the extreme differences in the x and y
>> dimensions, which alter the length of a and b, or for some other reason.
>>
> cov<- cov.matrix(20000, 0.4, 20)
>
> While this gives what looks like an almost entirely vertical line, using
> a much smaller angle
>
> cov<- cov.matrix(20000, .25, 0.0005)
>
> actually results in a sensible rotation, of about 20 degrees. So it
> looks like it works, but the scaling of the angle is wrong--it's far too
> sensitive. I'm correctly converting from degrees to radians, so I'm not
> sure why 8.7e-6 radians actually results in a rotation of ~0.35 radians!
>
>
> Regards,
> Roger
>
>
--
Josef Spidlen, Ph.D.
Terry Fox Laboratory, BC Cancer Agency
675 West 10th Avenue, V5Z 1L3 Vancouver, BC, Canada
Tel: +1 (604) 675-8000 x 7755
http://www.terryfoxlab.ca/people/rbrinkman/josef.aspx
------------------------------
Message: 18
Date: Wed, 15 Sep 2010 22:07:10 +0200
From: Adam Woznica <Adam.Woznica at unige.ch>
To: bioconductor at stat.math.ethz.ch
Subject: [BioC] e-LICO multi-omics prediction challenge with
background knowledge on Obstructive Nephropathy
Message-ID: <4C91276E.4030607 at unige.ch>
Content-Type: text/plain; CHARSET=US-ASCII; format=flowed
Dear all,
We present a biological data-mining problem that poses a number of
significant challenges; the available data: (i) are of high
dimensionality but of extremely small sample size, (ii) come from
different sources which correspond to different biological levels, (iii)
exhibit a high degree of feature dependencies and interactions within
and between the different sources; some of the interactions between the
different sources are known and available as background knowledge, and
(iv) are incomplete.
This data was obtained from patients with Obstructive Nephropathy (ON)
which is the most frequent nephropathy observed among newborns and
children, and the first cause of end stage renal disease usually treated
by dialysis or transplantation. The goal is to construct diagnostic
models that accurately connect the biological levels to the severity of
the pathology. We particularly welcome data mining approaches and
learning methods that are able to accommodate the available background
information in order to address the formidable challenge of high
dimensionality small sample size of our setting and deliver better models.
A prize is envisaged for the top performing approaches (2500EU in
total). The price is sponsored by Rapid-I the company that supports
RapidMiner, probably the most popular open-source data mining
environment, and the European Commission through the e-Lico EU project.
Participants are expected to prepare a paper, maximum 8 pages,
describing their approach. We plan to have a number of selected papers
considered for publication in a special issue of a journal (to be
announced soon).
Challenge web page: http://tunedit.org/challenge/ON .
Started: Sep 15, 2010
Ends: Dec 19, 2010
Organizing Committee:
- Alexandros Kalousis, University of Geneva, Switzerland
- Julie Klein, Inserm U858, Toulouse, France
- Joost Schanstra, Inserm U858, Toulouse, France
- Adam Woznica, University of Geneva, Switzerland
Regards,
Adam Woznica
------------------------------
Message: 19
Date: Wed, 15 Sep 2010 16:17:25 -0400
From: Steve Lianoglou <mailinglist.honeypot at gmail.com>
To: Elizabeth Ashley <elizabeth.ashley at linacre.ox.ac.uk>
Cc: "bioconductor at stat.math.ethz.ch" <bioconductor at stat.math.ethz.ch>
Subject: Re: [BioC] Querying clustering in heatmap.2
Message-ID:
<AANLkTinnLzAFVGaqPWKTqP1uAq_EK5HG-f0P1aFz==Eq at mail.gmail.com>
Content-Type: text/plain; charset=ISO-8859-1
Hi Lizzy,
On Wed, Sep 15, 2010 at 7:59 AM, Elizabeth Ashley
<elizabeth.ashley at linacre.ox.ac.uk> wrote:
> Hi
>
> I have used heatmap.2 to create a heatmap of my data. It automatically
clusters the data and I can't identify which part of the text does this.
However I am quite happy to have the clustering (of GO categories) but would
like to be able to query the groupings to find insights into how it is
clustered. Are these clusters named, and if so can you find out which ones
bring back significant data? Below is the script I am using.
I don't really know what type of data is in your GO matrix, nor do I
understand how you intend to find out "which ones bring back
significant data" but an answer to your more general question is to
look at the help from the heatmap.2 function: "?heatmap.2"
Scroll down to the "Value" section, and you'll see that there is a
list/structure that is returned "invisibly" (see ?invisible). There
are two elements in the list named "rowInd" and "colInd" as well as
"rowDendogram" and "colDendrogram" which you can use to start
investigating which rows + cols are grouping together.
Hope that helps,
-steve
--
Steve Lianoglou
Graduate Student: Computational Systems Biology
?| Memorial Sloan-Kettering Cancer Center
?| Weill Medical College of Cornell University
Contact Info: http://cbio.mskcc.org/~lianos/contact
------------------------------
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