## User: Claus Mayer

Claus Mayer •

**330**- Reputation:
**330**- Status:
- Trusted
- Location:
- European Union
- Last seen:
- 5 years ago
- Joined:
- 14 years, 6 months ago
- Email:
- c****@bioss.ac.uk

#### Posts by Claus Mayer

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... Hello!
I am working on a data set using C-difficile two-color microarrays and
would
like to do some pathway analysis. KEGG has quite a number of pathways
for
this organism (see
http://www.genome.jp/kegg-
bin/show_organism?menu_type=pathway_maps&org=cdf),
but when I tried to access them with KEG ...

written 8.5 years ago by
Claus Mayer •

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Comment:
C: Reg: T-statistic using limma

... That Venn Diagram is not very interesting in your case. The intercept
will
(unless you centered the data for some reason) always be significant
and is
of little interest. The comparison you are interested is between the
groups.
The empty circle in the diagram just means that you have no genes
signi ...

written 9.6 years ago by
Claus Mayer •

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Answer:
A: Reg: T-statistic using limma

... It should be population.goups <-
factor(c(rep("LL",3),rep("Control",3))
The way you defined it, each array forms his own group (and thus you
have no
degrees of freedom left).
Claus
> -----Original Message-----
> From: bioconductor-bounces at stat.math.ethz.ch
> [mailto:bioconductor-bo ...

written 9.6 years ago by
Claus Mayer •

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Answer:
A: Limma and logistic regression

... Hi Dan!
I am sure there are better references for this but you can find some
discussion on the topic logistic regression vs t-test at this link:
http://udel.edu/~mcdonald/statlogistic.html .
In an ideal world you assume in a regression model that the
explanatory
variable is fixed by the experiment ...

written 9.6 years ago by
Claus Mayer •

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... Dear Ana,
To give Naomi some rest, perhaps I can help with some answers:
>
> 1. Now that you mention, I can see that the within array variability
> should be smaller then the technical variability,
> but I cannot understand why treating them as the same, should be
less
> statistica ...

written 9.7 years ago by
Claus Mayer •

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Answer:
A: MA plots + dye swap

... Hi Guido!
Additionally to what Wolfgang already wrote you might have a look at a
related thread on the mailing list, that was discussed just recently
(https://stat.ethz.ch/pipermail/bioconductor/2010-January/thread.html#
31254)
.
What you call "mirrored version" of the MA-Plot, corresponds to the
...

written 9.7 years ago by
Claus Mayer •

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... Hi David!
I haven't had many data sets like that but as far as I can see limma
is not
only capable of comparing groups but you can also have continuous
measurements as explanatory variables, i.e. fit a multiple regression
type
of model by defining the design as
Design<- model.matrix(~ var1 + va ...

written 9.7 years ago by
Claus Mayer •

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... Dear Michal!
You should include dye effect in your linear model (cf the limma guide
8.1.2
Dye Swaps). The normalization only removers an overall dye-effect but
typically that effect is slightly different from gene to gene.
Including the
dye effect in the model should remove this remaining gene-spec ...

written 9.8 years ago by
Claus Mayer •

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... Hello Michael,
I think there are some things you are confusing here. It is correct
that
SAM uses a permutation method to give q-values, i.e.estimates of the
FDR
one would obtain when thresholding at the given value of the
test-statistic. This is SAM's specific way of using the permutations
though. ...

written 11.0 years ago by
Claus Mayer •

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Comment:
C: Question about F test in limma

... Dear Lisa,
no this is not a chance finding. Whether you include all 3 possible
contrasts or just the two you specify below: if all contrasts are zero
this is equivalent to the overall null hypothesis that all 3 treatment
means are the same, i.e. the F-test is testing the same hypothesis in
both ca ...

written 11.5 years ago by
Claus Mayer •

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