## User: Paul Harrison

Paul Harrison •

**70**- Reputation:
**70**- Status:
- Trusted
- Location:
- Australia/Melbourne/Monash University Bioinformatics Platform
- Website:
- http://logarithmic.net...
- Twitter:
- @paulfharrison
- Scholar ID:
- Google Scholar Page
- Last seen:
- 7 months, 1 week ago
- Joined:
- 6 years, 10 months ago
- Email:
- p************@monash.edu

#### Posts by Paul Harrison

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... Ok, it's important not to guess wrong. I'll require the user to do something explicitly marking the assays appropriate to use.
I think my solution will be to add some metadata fields to a SummarizedExperiment defining the appropriate pair of assays to use. I'll then write my code to produce an erro ...

written 9 months ago by
Paul Harrison •

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... Thanks Davide and Aaron. I had not thought about the distinction between frequencies and precision weights. So if I'm understanding correctly, `zinbwave` weights can be thought of as (fractional) frequencies, and contribute to the degrees of freedom as such. Also importantly, they are for `"counts"` ...

written 10 months ago by
Paul Harrison •

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... It looks like `SingleCellExperiment` has a `weights()` method, which is hopeful but I'm not clear on which assay the weights are meant to be associated with with. ...

written 11 months ago by
Paul Harrison •

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I am trying to work out the best way to represent weights in the newer `SummarizedExperiment` and `SingleCellExperiment` classes.
By weights I mean inverse variance (up to some scaling factor) for example as accepted by the `lm()` function. Weights are a somewhat simplistic but general way of acco ...

written 11 months ago by
Paul Harrison •

**70**• updated 11 months ago by davide risso •**830**0

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... Since RNA-seq is count based, in an RNA-seq analysis at the gene level the noise in individual counts for genes can be assumed to be Poisson (variance equal to the mean). This is an estimate of "technical variation", but does not include "biological varation". This would be the equivalent of the Kal ...

written 2.2 years ago by
Paul Harrison •

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Comment:
C: Limma-voom vs limma-trend

... If you examine the documentation to `contrasts.fit`, there is a warning that using weights with a non-orthogonal design matrix uses an approximation. Since voom uses weights on inidividual observations, and limma-trend does not, this could be an advantage to using limma-trend.
...

written 2.4 years ago by
Paul Harrison •

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... limma's barcodeplot function by default draws a pale red rectangle for statistics greater than sqrt(2) and a pale blue rectangle for statistics less than -sqrt(2). What is the reasoning is behind this choice?
Is the expectation that statistics follows a standard normal distribution for genes that a ...

written 3.3 years ago by
Paul Harrison •

**70**• updated 3.3 years ago by Gordon Smyth ♦**39k**0

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Comment:
C: Behaviour of weights in limma

... On Thu, Jun 5, 2014 at 10:04 AM, Gordon K Smyth
wrote:
> Dear Paul,
>
>> Date: Wed, 4 Jun 2014 17:30:59 +1000
>> From: Paul Harrison
>> To: Bioconductor mailing list
>> Subject: [BioC] Behaviour of weights in limma
>>
>> Hello,
>>
>> I have so ...

written 5.5 years ago by
Paul Harrison •

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... Hello,
I have some data from a variant of RNA-seq which I am hoping do some
moderated t-test differential testing on with limma. In this data,
many of the reads have sequenced through into the poly(A) tail, and we
believe this gives us information about changes in poly(A) tail
length.
For each gen ...

written 5.5 years ago by
Paul Harrison •

**70**• updated 5.5 years ago by Gordon Smyth ♦**39k**0

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... On Mon, Feb 4, 2013 at 7:56 PM, Wolfgang Huber
wrote:
>
> Hi Paul
>
> the model (in the "parametric" case) is
>
> var(X) = a * E(X) + b * E(X)^2
>
> with some a,b>0. And you are right that var(X)=0 <=> E(X)=0
> but since the support of X is positive, the onl ...

written 6.9 years ago by
Paul Harrison •

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