Hi Bioconductor folks,
I have really been enjoying using the limma package, but I have just
come
across a problem.
When I use the topTable-command, the slot "result$Probe.Set.ID" does
not seem
to match the other entries I am interested in, namely M, P, t.
I am using R 1.8.0, limma 1.5.5 on Affymetrix ATH1-121501 chips.
An example would be:
Output of the topTable-result:
Probe.Set.ID M t
P.Value B
5598 259302_at 4.593339 38.9793 1.126260e-05 11.88238
If I check on gene number 5598 it says
geneNames(myExprSet)[5598]
[1] "250498_at"
Am I misinterpreting 5598 as the index of my ExpressionSet?
Thanks a lot for any suggestions!
Julia
At 02:32 AM 19/03/2004, Julia Engelmann wrote:
>Hi Bioconductor folks,
>
>I have really been enjoying using the limma package, but I have just
come
>across a problem.
>When I use the topTable-command, the slot "result$Probe.Set.ID" does
not seem
>to match the other entries I am interested in, namely M, P, t.
>I am using R 1.8.0, limma 1.5.5 on Affymetrix ATH1-121501 chips.
>
>An example would be:
>Output of the topTable-result:
>
> Probe.Set.ID M t
> P.Value B
>5598 259302_at 4.593339 38.9793 1.126260e-05 11.88238
>
>If I check on gene number 5598 it says
>geneNames(myExprSet)[5598]
>[1] "250498_at"
>
>Am I misinterpreting 5598 as the index of my ExpressionSet?
I think you've done something non-standard, anyway you can't have
simply
used lmFit() and eBayes() and topTable() on our exprSet object. Please
show
us enough of your code so that we can see how topTable is getting the
probe
set ID's.
Gordon
>Thanks a lot for any suggestions!
>Julia
Sorry, here comes my code:
library(affy)
library(limma)
library(vsn)
data <- ReadAffy()
normalize.AffyBatch.methods <- c(normalize.AffyBatch.methods, "vsn")
Set <- expresso(data, normalize.method="vsn",
bgcorrect.method="none",pmcorrect.method="pmonly",
summary.method="medianpolish")
# R and T stand for different treatment, R1 and R2 as well as T1 and
T2 are
biological reps.
design <- model.matrix(~ -1+factor(c(1,1,2,2,3,3,4,4)))
colnames(design) <- c("R1","R2","T1","T2")
fit <- lmFit(Set, design)
contrast.matrix <- makeContrasts(((R1+R2)-(T1
+T2))/2,R1-T1,R2-T2,levels=design);
fit2 <- contrasts.fit(fit, contrast.matrix)
fit2 <- eBayes(fit2)
data <- read.table("ATH1-121501_annot.csv", header=TRUE,
sep=",")
res <- topTable(fit2, number=10,coef=1,
adjust="fdr",genelist=data,sort.by="P",resort.by="M")
Thanks a lot again,
Julia
> >Hi Bioconductor folks,
> >
> >I have really been enjoying using the limma package, but I have
just come
> >across a problem.
> >When I use the topTable-command, the slot "result$Probe.Set.ID"
does not
> > seem to match the other entries I am interested in, namely M, P,
t.
> >I am using R 1.8.0, limma 1.5.5 on Affymetrix ATH1-121501 chips.
> >
> >An example would be:
> >Output of the topTable-result:
> >
> > Probe.Set.ID M t
> > P.Value B
> >5598 259302_at 4.593339 38.9793 1.126260e-05 11.88238
> >
> >If I check on gene number 5598 it says
> >geneNames(myExprSet)[5598]
> >[1] "250498_at"
> >
> >Am I misinterpreting 5598 as the index of my ExpressionSet?
>
> I think you've done something non-standard, anyway you can't have
simply
> used lmFit() and eBayes() and topTable() on our exprSet object.
Please show
> us enough of your code so that we can see how topTable is getting
the probe
> set ID's.
>
> Gordon
>
> >Thanks a lot for any suggestions!
> >Julia
> Sorry, here comes my code:
>
> library(affy)
> library(limma)
> library(vsn)
> data <- ReadAffy()
> normalize.AffyBatch.methods <- c(normalize.AffyBatch.methods, "vsn")
> Set <- expresso(data, normalize.method="vsn",
> bgcorrect.method="none",pmcorrect.method="pmonly",
> summary.method="medianpolish")
>
> # R and T stand for different treatment, R1 and R2 as well as T1 and
T2
> are biological reps.
> design <- model.matrix(~ -1+factor(c(1,1,2,2,3,3,4,4)))
> colnames(design) <- c("R1","R2","T1","T2")
> fit <- lmFit(Set, design)
> contrast.matrix <- makeContrasts(((R1+R2)-(T1
> +T2))/2,R1-T1,R2-T2,levels=design);
> fit2 <- contrasts.fit(fit, contrast.matrix)
> fit2 <- eBayes(fit2)
> data <- read.table("ATH1-121501_annot.csv", header=TRUE,
> sep=",") res <- topTable(fit2, number=10,coef=1,
> adjust="fdr",genelist=data,sort.by="P",resort.by="M")
Mmmm, it appears that the genes are a different order in your data
object
'Set' compared to your annotation file read into 'data'. Just use
genelist=geneNames(Set)
in the topTable argument list to ensure you're using the right names.
>From limma 1.5.8, topTable will extract the IDs directly from the
exprSet
object so you won't have to input the names yourself.
Gordon
> Thanks a lot again,
> Julia
>
>> >Hi Bioconductor folks,
>> >
>> >I have really been enjoying using the limma package, but I have
just
>> come across a problem.
>> >When I use the topTable-command, the slot "result$Probe.Set.ID"
does
>> not
>> > seem to match the other entries I am interested in, namely M, P,
t.
>> >I am using R 1.8.0, limma 1.5.5 on Affymetrix ATH1-121501 chips.
>> >
>> >An example would be:
>> >Output of the topTable-result:
>> >
>> > Probe.Set.ID M t
>> > P.Value B
>> >5598 259302_at 4.593339 38.9793 1.126260e-05 11.88238
>> >
>> >If I check on gene number 5598 it says
>> >geneNames(myExprSet)[5598]
>> >[1] "250498_at"
>> >
>> >Am I misinterpreting 5598 as the index of my ExpressionSet?
>>
>> I think you've done something non-standard, anyway you can't have
>> simply used lmFit() and eBayes() and topTable() on our exprSet
object.
>> Please show us enough of your code so that we can see how topTable
is
>> getting the probe set ID's.
>>
>> Gordon
>>
>> >Thanks a lot for any suggestions!
>> >Julia
>
> _______________________________________________
> Bioconductor mailing list
> Bioconductor@stat.math.ethz.ch
> https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
Hi all,
I have the following expression:
P(J=j)= [1/(2^(2N-m))]*[Combination(2N-m; n-i)* Combination(m; i)] /
Combination(N; n)
It is similar to the hypergeometric distribution but it is not. Can
anyone
tell me whether this is a known distribution (I cannot find anything
that
looks like it).
Can this be written as an H-function or hypergeometric function? (it
seems
to me that it is not, however, any suggestions are appreciated)
Thanks for your help,
Mike
----------------------
E Motakis, Mathematics
E.Motakis@bristol.ac.uk
