Even if the signal given by the histogram is not really a signal, it seems
that spec.pgram can give an interesting evaluation of how the genes are
spaced in the chromosome, like in the article.
So now, when I study a chromosome with 200 interesting genes, I would like
to compare the amplitude of th
OK, it seems like I do not succeed in expressing what I do, or want to do.
So, I give you the example that bring me to this kind of analysis. I wrote
the paper "Chromosomal periodicity of evolutionary conserved gene pairs"
(which you can download at http://www.pnas.org/cgi/reprint/104/25/10559). In
To get some sort of frequency which in your case seem to be cycles per
distance? Is a valid use of a fourier transform as long as it is a distance
that is measured in a way that would be analogous to a time series- In
other words if the distance proceeds from an origin in one direction-
geophysic
Perhaps I'm applying spec.pgram wrong as you said. I will explain what I
want, so you can tell me why I'm wrong and perhaps what I have to do to do
it well.
I have some points in a 1-D space and I want to know if they are spaced at a
certain periodic distance. So, I computed all the distances betwe
I from a first thought I would say that you are apply this wrong! The
fourier transform convolves a function (cos(x)+isin(x) (this may not be the
exact formula but I don't have my books near)) to the data and then
integrates over -1/2 to 1/2 takes the modulus and plots this- the
periodogram. The
Hello
I don't know exactly what you want to do but:
-why do you use in your example h$counts and not h? Furthermore helpl
file says it should be a time series, why then rather not your time series?
-usually na.action will make the "default" action, which you can see by
getOptions("na.action"
Hi everyone,
first of all, I would like to say that I am a newbie in R, so I apologize in
advance if my questions seem to be too easy for you.
Well, I'm looking for periodicity in histograms. I have histograms of
certain phenomenons and I'm asking whether a periodicity exists in these
data. So, I
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