Dear R-users, I intend to do a spatial analysis on the genetic structuring within a population. For this I had thought to prepare a kernel density estimate map showing the spatial distribution of individuals, while incorporating the genetic distances among individuals. I have a dataset of locations of N unique individuals (XY-coordinates) and an NxN matrix with the genetic distances given as a fraction between 0 and 1. As far as I understand the methodology, a kernel density estimate works with the geographic distance matrix. My idea was to somehow incorporate the genetic distance matrix (e.g. as an among-individual-based smoothing factor???) in the estimation. Does anyone know if this is possible? To me it sounds a logical inclusion which may be interesting for a wide variety of topics (i.e., "not all individuals are equal"). I hope someone knows of any way to proceed. Thanks in advance, Cheers Roel May Roel May Norwegian Institute for Nature Research (NINA) Tungasletta 2, NO-7485 Trondheim, Norway Tlf. +47 73 80 14 65, Mob. +47 95 78 59 95 Email roel.may at nina.no Internett www.nina.no, www.jerv.info
If you don't insist on kernel smoothing, and are willing to use something similar, locfit() in the locfit package uses local likelihood to estimate density and can accept weights. E.g., library(locfit) plot(locfit(~Petal.Length + Petal.Width, data=iris)) plot(locfit(~Petal.Length + Petal.Width, data=iris, weights=rep(1:3, each=50))) Andy From: May, Roel> > Dear R-users, > > I intend to do a spatial analysis on the genetic structuring > within a population. For this I had thought to prepare a > kernel density estimate map showing the spatial distribution > of individuals, while incorporating the genetic distances > among individuals. I have a dataset of locations of N unique > individuals (XY-coordinates) and an NxN matrix with the > genetic distances given as a fraction between 0 and 1. As far > as I understand the methodology, a kernel density estimate > works with the geographic distance matrix. My idea was to > somehow incorporate the genetic distance matrix (e.g. as an > among-individual-based smoothing > factor???) in the estimation. Does anyone know if this is > possible? To me it sounds a logical inclusion which may be > interesting for a wide variety of topics (i.e., "not all > individuals are equal"). I hope someone knows of any way to > proceed. Thanks in advance, > > > Cheers Roel May > > > Roel May > Norwegian Institute for Nature Research (NINA) > Tungasletta 2, NO-7485 Trondheim, Norway > Tlf. +47 73 80 14 65, Mob. +47 95 78 59 95 > Email roel.may at nina.no > Internett www.nina.no, www.jerv.info > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > >
On Thu, 2006-04-06 at 14:29 +0200, May, Roel wrote:> Dear R-users, > > I intend to do a spatial analysis on the genetic structuring within a > population. For this I had thought to prepare a kernel density estimate > map showing the spatial distribution of individuals, while incorporating > the genetic distances among individuals. I have a dataset of locations > of N unique individuals (XY-coordinates) and an NxN matrix with the > genetic distances given as a fraction between 0 and 1. As far as I > understand the methodology, a kernel density estimate works with the > geographic distance matrix. My idea was to somehow incorporate the > genetic distance matrix (e.g. as an among-individual-based smoothing > factor???) in the estimation. Does anyone know if this is possible? To > me it sounds a logical inclusion which may be interesting for a wide > variety of topics (i.e., "not all individuals are equal"). I hope > someone knows of any way to proceed. Thanks in advance, > >Dear Roel -- it is not entirely clear what you wish to achieve. Sampling weights associated with a unit can be incorporated at least in the locfit package, which also allows you to do a 2-dimensional density estimate, but this does not sound like what you are interested in.>From your description, it sounds like you have a data set which consistsof 1/2*N*(N-1) unique pairs of individuals with data x1 y1 x2 y2 w where (x1, y1) and (x2, y2) are the (x,y) coordinates and w is the genetic distance between the two (there are only 1/2*N*(N-1) on the assumption that the genetic distance for any i,j individuals is symmetric so w(i,j) = w(j, i) and w(i, i) = 1). Are you interested in plotting on a map of (x, y) coordinates some measure of how genetically related the population at the that coordinate are with their surroundinds? I.e., value at x1, y1 of w summarised by a kernel function over all x2, y2? Best wishes, Markus> Cheers Roel May > > > Roel May > Norwegian Institute for Nature Research (NINA) > Tungasletta 2, NO-7485 Trondheim, Norway > Tlf. +47 73 80 14 65, Mob. +47 95 78 59 95 > Email roel.may at nina.no > Internett www.nina.no, www.jerv.info > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide!http://www.R-project.org/posting-guide.html -- Markus Jantti Abo Akademi University markus.jantti at iki.fi http://www.iki.fi/~mjantti ########################################### This message has been scanned by F-Secure Anti-Virus for Mic...{{dropped}}
Dear Markus, I indeed have a data set consisting of 1/2*N*(N-1) unique pairs of individuals with data x1 y1 x2 y2 w I am however not interested in, like you said, the value at x1, y1 of w summarised by a kernel function over all x2, y2 (if I understand you rightly that is...). This sounds like doing a weighted kernel density estimate as seen from the 'viewpoint' of a certain location/individual. I know could be done with sm.density in the sm library. I am interested to create a map depicted the total structuring in the entire population (both based on geographic and genetic distances). This means that the evaluation/interpolation at each location have to take into account both the geographic AND the genetic distance matrix (both with 1/2*N*(N-1) unique combinations). To clarify myself a bit more, such a map could show for example differentiation in the population (of wolverines by the way) because of large geographic distances OR because of large genetic distances. I have quickly checked locfit but I am not sure if this would work for me. Roel -----Original Message----- From: Markus Jantti [mailto:markus.jantti at iki.fi] Sent: 6. april 2006 14:56 To: r-help at stat.math.ethz.ch Cc: May, Roel Subject: Re: [R] weighted kernel density estimate On Thu, 2006-04-06 at 14:29 +0200, May, Roel wrote:> Dear R-users, > > I intend to do a spatial analysis on the genetic structuring within a > population. For this I had thought to prepare a kernel density > estimate map showing the spatial distribution of individuals, while > incorporating the genetic distances among individuals. I have a > dataset of locations of N unique individuals (XY-coordinates) and an > NxN matrix with the genetic distances given as a fraction between 0 > and 1. As far as I understand the methodology, a kernel density > estimate works with the geographic distance matrix. My idea was to > somehow incorporate the genetic distance matrix (e.g. as an > among-individual-based smoothing > factor???) in the estimation. Does anyone know if this is possible? To> me it sounds a logical inclusion which may be interesting for a wide > variety of topics (i.e., "not all individuals are equal"). I hope > someone knows of any way to proceed. Thanks in advance, > >Dear Roel -- it is not entirely clear what you wish to achieve. Sampling weights associated with a unit can be incorporated at least in the locfit package, which also allows you to do a 2-dimensional density estimate, but this does not sound like what you are interested in.>From your description, it sounds like you have a data set which >consistsof 1/2*N*(N-1) unique pairs of individuals with data x1 y1 x2 y2 w where (x1, y1) and (x2, y2) are the (x,y) coordinates and w is the genetic distance between the two (there are only 1/2*N*(N-1) on the assumption that the genetic distance for any i,j individuals is symmetric so w(i,j) = w(j, i) and w(i, i) = 1). Are you interested in plotting on a map of (x, y) coordinates some measure of how genetically related the population at the that coordinate are with their surroundinds? I.e., value at x1, y1 of w summarised by a kernel function over all x2, y2? Best wishes, Markus> Cheers Roel May > > > Roel May > Norwegian Institute for Nature Research (NINA) Tungasletta 2, NO-7485 > Trondheim, Norway Tlf. +47 73 80 14 65, Mob. +47 95 78 59 95 Email > roel.may at nina.no Internett www.nina.no, www.jerv.info > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide!http://www.R-project.org/posting-guide.html -- Markus Jantti Abo Akademi University markus.jantti at iki.fi http://www.iki.fi/~mjantti ########################################### This message has been scanned by F-Secure Anti-Virus for Mic...{{dropped}}