heatmap.2
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carol white ▴ 680
@carol-white-2174
Last seen 9.0 years ago
European Union
Hi, Does heatmap.2 function combine all variables into a single overall measure of dissimilarity between two observations as explained in The elements of statistical learning, Hastie et al, 2001, pp457? Does this function calculate the dissimilarity between observations and variables as follows? N N p 1/(N^2) sum sum sum d(xij,xi'j) i=1 i'=1 j=1 where N is the number of observations, p the number of variables, xi and xi' are two different observations, and d is the dissimilarity between two variables, respectively. Any relevant information is welcome. Best, Carol
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@sean-davis-490
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On Wed, Apr 28, 2010 at 4:36 AM, carol white <wht_crl at="" yahoo.com=""> wrote: > Hi, > Does heatmap.2 function combine all variables into a single overall measure of dissimilarity between two observations as explained in The elements of statistical learning, Hastie et al, 2001, pp457? Does this function calculate the dissimilarity between observations and variables as follows? > > ? ? ? ? N ? N ? ?p > 1/(N^2) sum sum ? sum d(xij,xi'j) > ? ? ? ?i=1 i'=1 ?j=1 > > where N is the number of observations, p the number of variables, xi and xi' are two different observations, and d is the dissimilarity between two variables, respectively. > > Any relevant information is welcome. Hi, Carol. The first place to stop when asking these types of questions is the help system. help(heatmap.2) shows that the default distance function used is "dist". Checking help(dist) reveals that there are many options for distance measurement, but the default is "euclidean". There are a number of examples and even a couple of references. Hope that helps. Sean
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Thanks Sean for your reply. Actually the question was not on the distance measure. What I wanted to know how the clustering is performed on two dimensions. Is the dissimilary function (whatever it is, euclidean, pearson correlation, etc) is performed on all variables and then, on the observations or any other way? Is it more clear? Best, --- On Wed, 4/28/10, Sean Davis <seandavi at="" gmail.com=""> wrote: > From: Sean Davis <seandavi at="" gmail.com=""> > Subject: Re: [BioC] heatmap.2 > To: "carol white" <wht_crl at="" yahoo.com=""> > Cc: bioconductor at stat.math.ethz.ch > Date: Wednesday, April 28, 2010, 3:55 AM > On Wed, Apr 28, 2010 at 4:36 AM, > carol white <wht_crl at="" yahoo.com=""> > wrote: > > Hi, > > Does heatmap.2 function combine all variables into a > single overall measure of dissimilarity between two > observations as explained in The elements of statistical > learning, Hastie et al, 2001, pp457? Does this function > calculate the dissimilarity between observations and > variables as follows? > > > > ? ? ? ? N ? N ? ?p > > 1/(N^2) sum sum ? sum d(xij,xi'j) > > ? ? ? ?i=1 i'=1 ?j=1 > > > > where N is the number of observations, p the number of > variables, xi and xi' are two different observations, and d > is the dissimilarity between two variables, respectively. > > > > Any relevant information is welcome. > > Hi, Carol. > > The first place to stop when asking these types of > questions is the > help system.? help(heatmap.2) shows that the default > distance function > used is "dist".? Checking help(dist) reveals that > there are many > options for distance measurement, but the default is > "euclidean". > There are a number of examples and even a couple of > references. > > Hope that helps. > > Sean >
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On Wed, Apr 28, 2010 at 3:52 PM, carol white <wht_crl at="" yahoo.com=""> wrote: > Thanks Sean for your reply. > > Actually the question was not on the distance measure. What I wanted to know how the clustering is performed on two dimensions. Is the dissimilary function (whatever it is, euclidean, pearson correlation, etc) is performed on all variables and then, on the observations or any other way? > > Is it more clear? Sorry I misunderstood. The clustering is done independently in each dimension. The plot is where the two dimensions are combined. Sean > --- On Wed, 4/28/10, Sean Davis <seandavi at="" gmail.com=""> wrote: > >> From: Sean Davis <seandavi at="" gmail.com=""> >> Subject: Re: [BioC] heatmap.2 >> To: "carol white" <wht_crl at="" yahoo.com=""> >> Cc: bioconductor at stat.math.ethz.ch >> Date: Wednesday, April 28, 2010, 3:55 AM >> On Wed, Apr 28, 2010 at 4:36 AM, >> carol white <wht_crl at="" yahoo.com=""> >> wrote: >> > Hi, >> > Does heatmap.2 function combine all variables into a >> single overall measure of dissimilarity between two >> observations as explained in The elements of statistical >> learning, Hastie et al, 2001, pp457? Does this function >> calculate the dissimilarity between observations and >> variables as follows? >> > >> > ? ? ? ? N ? N ? ?p >> > 1/(N^2) sum sum ? sum d(xij,xi'j) >> > ? ? ? ?i=1 i'=1 ?j=1 >> > >> > where N is the number of observations, p the number of >> variables, xi and xi' are two different observations, and d >> is the dissimilarity between two variables, respectively. >> > >> > Any relevant information is welcome. >> >> Hi, Carol. >> >> The first place to stop when asking these types of >> questions is the >> help system.? help(heatmap.2) shows that the default >> distance function >> used is "dist".? Checking help(dist) reveals that >> there are many >> options for distance measurement, but the default is >> "euclidean". >> There are a number of examples and even a couple of >> references. >> >> Hope that helps. >> >> Sean >> > > > >
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How are they combined? So my formula was not correct? Any reference, documentation of the performed steps (general description and/or math description)? Many thanks --- On Wed, 4/28/10, Sean Davis <seandavi at="" gmail.com=""> wrote: > From: Sean Davis <seandavi at="" gmail.com=""> > Subject: Re: [BioC] heatmap.2 > To: "carol white" <wht_crl at="" yahoo.com=""> > Cc: bioconductor at stat.math.ethz.ch > Date: Wednesday, April 28, 2010, 12:56 PM > On Wed, Apr 28, 2010 at 3:52 PM, > carol white <wht_crl at="" yahoo.com=""> > wrote: > > Thanks Sean for your reply. > > > > Actually the question was not on the distance measure. > What I wanted to know how the clustering is performed on two > dimensions. Is the dissimilary function (whatever it is, > euclidean, pearson correlation, etc) is performed on all > variables and then, on the observations or any other way? > > > > Is it more clear? > > Sorry I misunderstood.? The clustering is done > independently in each > dimension.? The plot is where the two dimensions are > combined. > > Sean > > > > --- On Wed, 4/28/10, Sean Davis <seandavi at="" gmail.com=""> > wrote: > > > >> From: Sean Davis <seandavi at="" gmail.com=""> > >> Subject: Re: [BioC] heatmap.2 > >> To: "carol white" <wht_crl at="" yahoo.com=""> > >> Cc: bioconductor at stat.math.ethz.ch > >> Date: Wednesday, April 28, 2010, 3:55 AM > >> On Wed, Apr 28, 2010 at 4:36 AM, > >> carol white <wht_crl at="" yahoo.com=""> > >> wrote: > >> > Hi, > >> > Does heatmap.2 function combine all variables > into a > >> single overall measure of dissimilarity between > two > >> observations as explained in The elements of > statistical > >> learning, Hastie et al, 2001, pp457? Does this > function > >> calculate the dissimilarity between observations > and > >> variables as follows? > >> > > >> > ? ? ? ? N ? N ? ?p > >> > 1/(N^2) sum sum ? sum d(xij,xi'j) > >> > ? ? ? ?i=1 i'=1 ?j=1 > >> > > >> > where N is the number of observations, p the > number of > >> variables, xi and xi' are two different > observations, and d > >> is the dissimilarity between two variables, > respectively. > >> > > >> > Any relevant information is welcome. > >> > >> Hi, Carol. > >> > >> The first place to stop when asking these types > of > >> questions is the > >> help system.? help(heatmap.2) shows that the > default > >> distance function > >> used is "dist".? Checking help(dist) reveals > that > >> there are many > >> options for distance measurement, but the default > is > >> "euclidean". > >> There are a number of examples and even a couple > of > >> references. > >> > >> Hope that helps. > >> > >> Sean > >> > > > > > > > > >
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On Wed, Apr 28, 2010 at 4:01 PM, carol white <wht_crl at="" yahoo.com=""> wrote: > How are they combined? So my formula was not correct? Any reference, documentation of the performed steps (general description and/or math description)? The columns are ordered according to a dendrogram produced for the samples; the rows are ordered according to a dendrogram produced for the genes. There is no "combination" that occurs. One of the first papers describing heatmaps applied in a microarray context is here: http://www.ncbi.nlm.nih.gov/pubmed/9843981 Hope that helps. Sean > --- On Wed, 4/28/10, Sean Davis <seandavi at="" gmail.com=""> wrote: > >> From: Sean Davis <seandavi at="" gmail.com=""> >> Subject: Re: [BioC] heatmap.2 >> To: "carol white" <wht_crl at="" yahoo.com=""> >> Cc: bioconductor at stat.math.ethz.ch >> Date: Wednesday, April 28, 2010, 12:56 PM >> On Wed, Apr 28, 2010 at 3:52 PM, >> carol white <wht_crl at="" yahoo.com=""> >> wrote: >> > Thanks Sean for your reply. >> > >> > Actually the question was not on the distance measure. >> What I wanted to know how the clustering is performed on two >> dimensions. Is the dissimilary function (whatever it is, >> euclidean, pearson correlation, etc) is performed on all >> variables and then, on the observations or any other way? >> > >> > Is it more clear? >> >> Sorry I misunderstood.? The clustering is done >> independently in each >> dimension.? The plot is where the two dimensions are >> combined. >> >> Sean >> >> >> > --- On Wed, 4/28/10, Sean Davis <seandavi at="" gmail.com=""> >> wrote: >> > >> >> From: Sean Davis <seandavi at="" gmail.com=""> >> >> Subject: Re: [BioC] heatmap.2 >> >> To: "carol white" <wht_crl at="" yahoo.com=""> >> >> Cc: bioconductor at stat.math.ethz.ch >> >> Date: Wednesday, April 28, 2010, 3:55 AM >> >> On Wed, Apr 28, 2010 at 4:36 AM, >> >> carol white <wht_crl at="" yahoo.com=""> >> >> wrote: >> >> > Hi, >> >> > Does heatmap.2 function combine all variables >> into a >> >> single overall measure of dissimilarity between >> two >> >> observations as explained in The elements of >> statistical >> >> learning, Hastie et al, 2001, pp457? Does this >> function >> >> calculate the dissimilarity between observations >> and >> >> variables as follows? >> >> > >> >> > ? ? ? ? N ? N ? ?p >> >> > 1/(N^2) sum sum ? sum d(xij,xi'j) >> >> > ? ? ? ?i=1 i'=1 ?j=1 >> >> > >> >> > where N is the number of observations, p the >> number of >> >> variables, xi and xi' are two different >> observations, and d >> >> is the dissimilarity between two variables, >> respectively. >> >> > >> >> > Any relevant information is welcome. >> >> >> >> Hi, Carol. >> >> >> >> The first place to stop when asking these types >> of >> >> questions is the >> >> help system.? help(heatmap.2) shows that the >> default >> >> distance function >> >> used is "dist".? Checking help(dist) reveals >> that >> >> there are many >> >> options for distance measurement, but the default >> is >> >> "euclidean". >> >> There are a number of examples and even a couple >> of >> >> references. >> >> >> >> Hope that helps. >> >> >> >> Sean >> >> >> > >> > >> > >> > >> > > > >
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