Hi,
what is the exact problem? I tried you code and it works fine...
Best,
Kimmo
24.08.2016, 10:07, Serpil ŞEN wrote:
Dear Authorized Sir / Madam,
I need your help on clustering with R.
I have symmetric distance matrix which i created usign ClustalOmega program.
and used this R codes for cl
Dear Authorized Sir / Madam,
I need your help on clustering with R.
I have symmetric distance matrix which i created usign ClustalOmega program.
and used this R codes for clustering purpose.
*data=read.table("my_distance_matrix", header=FALSE)[-1]*
*attach(data)*
*head(data)*
*d=as.dist(data);*
I am not sure about your question but i did find this:
http://research.med.helsinki.fi/corefacilities/proteinchem/hierarchical_clustering_basics.pdf
it seems to address all three topics so perhaps the answer is in there??
On Mar 28, 2013, at 6:16 PM, Pierre Antoine DuBoDeNa wrote:
> Hello,
>
Anyone for that question?
2013/3/28 Pierre Antoine DuBoDeNa
> Hello,
>
> I want to use pearson's correlation as distance between observations and
> then use any centroid based linkage distance (ex. Ward's distance)
>
> When linkage distances are formed as the Lance-Williams recursive
> formul
Hello,
I want to use pearson's correlation as distance between observations and
then use any centroid based linkage distance (ex. Ward's distance)
When linkage distances are formed as the Lance-Williams recursive
formulation, they just require the initial distance between observations.
See here:
On Fri, Mar 09, 2012 at 08:26:01PM -0500, Massimo Di Stefano wrote:
> my target is to have 'groups of species' based on the similarity of theyr
> environmental parameters, and build a dendrogram like [2]
>
> [2] http://massimo-timecapsule.whoi.edu//data/img/manova_clust_matlab.png
> Il giorno M
i'll try to describe the data,
here [1] there is a subdatset (255 rows) 6 columns (a to f)
the last columns contains the Identification Number (ID) for a particular
species.
the ID in f are 20 different species and it should be my 'label':
16001
11012
25011
13011
11029
11027
10022
10024
20009
11
On Fri, Mar 9, 2012 at 1:50 PM, Massimo Di Stefano
wrote:
> Peter,
>
> really thanks for your answer.
>
>
>
> install.packages("flashClust")
> library(flashClust)
> data <- read.csv('/Users/epifanio/Desktop/cluster/x.txt')
> data <- na.omit(data)
> data <- scale(data)
>> mydata
>
Peter,
really thanks for your answer.
install.packages("flashClust")
library(flashClust)
data <- read.csv('/Users/epifanio/Desktop/cluster/x.txt')
data <- na.omit(data)
data <- scale(data)
> mydata
a bc d e
1 -0.207709346 -6.61855
On Thu, Mar 8, 2012 at 4:41 AM, Massimo Di Stefano
wrote:
>
> Hello All,
>
> i've a set of observations that is in the form :
>
> a, b, c, d, e, f
> 67.12, 4.28, 1.7825, 30, 3, 16001
> 67.12, 4.28, 1.7825, 30, 3, 16001
> 66.57, 4.28, 1.355, 30,
2012/3/9 Uwe Ligges :
> I think the main issue of the OP is that he geneartes a 55000x55000 distance
> matrix and has to calculate on it. Beside immense main memory consumption
> this may take ages to complete with hierarchical clustering.
Indeed. I missed that in the original email.
If a non-hie
I think the main issue of the OP is that he geneartes a 55000x55000
distance matrix and has to calculate on it. Beside immense main memory
consumption this may take ages to complete with hierarchical clustering.
Uwe Ligges
On 08.03.2012 15:02, Sarah Goslee wrote:
See inline:
On Thu, Mar 8,
See inline:
On Thu, Mar 8, 2012 at 7:41 AM, Massimo Di Stefano
wrote:
>
> Hello All,
>
> i've a set of observations that is in the form :
>
> a, b, c, d, e, f
> 67.12, 4.28, 1.7825, 30, 3, 16001
> 67.12, 4.28, 1.7825, 30, 3, 16001
> 66.57, 4.28,
Hello All,
i've a set of observations that is in the form :
a,b,c,d,e,f
67.12,4.28,1.7825,30,3,16001
67.12,4.28,1.7825,30,3,16001
66.57,4.28,1.355,30,3,16001
66.2,4.28,1.3459,13,3,16001
66.2,4
You can print out the nodes and their corresponding clusters into a file by
this:
> write.table (hc,file="hc_40clusters.cvs", quote=FALSE, sep=" ")
--
View this message in context:
http://r.789695.n4.nabble.com/hierarchical-clustering-within-a-size-limit-tp3515354p4080551.html
Sent from the R
Hi Peter,
Thanks for your help. A second simple question that I cannot solve is the
following.
labels = cutree(hc, h=500)
# members of cluster 1:
x[labels==1]
# members of cluster 2:
x[labels==2]
When x is >= 8 the index numbers appear in the output:
[['[1]', '180066408', '180066464', '18006646
On Wed, May 11, 2011 at 10:12 AM, rna seq wrote:
> Hello List,
>
> I am trying to implement a hierarchical cluster using the hclust method
> agglomerative single linkage method with a small wrinkle. I would like to
> cluster a set of numbers on a number line only if they are within a distance
> of
Hello List,
I am trying to implement a hierarchical cluster using the hclust method
agglomerative single linkage method with a small wrinkle. I would like to
cluster a set of numbers on a number line only if they are within a distance
of 500. I would then like to print out the members of this list
new...@r wrote:
>
> Hey Everyone!
>
> I wanted to carry out Hierarchical clustering using distance matrices i
> have calculated ( instead of euclidean distance etc.)
>
> I understand as.dist is the function for this, but the distances in the
> dendrogram i got by using the following script(1)
Hey Everyone!
I wanted to carry out Hierarchical clustering using distance matrices i have
calculated ( instead of euclidean distance etc.)
I understand as.dist is the function for this, but the distances in the
dendrogram i got by using the following script(1) were not the distances
defined in
Try "Jaccard". :-)
karuna m wrote:
hi,
I want to do hierarchical clustering with Jaccord index. I tried to do with vegan package
for finding index and hierarchical clustering with hclust function. While doing
clustering it is showing an error message as "invalid distance method". I would
be
hi,
I want to do hierarchical clustering with Jaccord index. I tried to do with
vegan package for finding index and hierarchical clustering with hclust
function. While doing clustering it is showing an error message as "invalid
distance method". I would be grateful if anyone tells how to rectify
n of eight procedures" Psychometrika, 73,1, 125-144
Thanx
Herry
-Original Message-
From: Dylan Beaudette [mailto:dylan.beaude...@gmail.com]
Sent: Wednesday, July 01, 2009 2:01 PM
To: Herr, Alexander Herr - Herry (CSE, Gungahlin)
Cc: r-help@r-project.org
Subject: Re: [R] hierarchical cluste
varclust() in the Hmisc package might be what you are looking for.
Dylan
On Tue, Jun 30, 2009 at 7:27 PM, wrote:
>
> Hi List,
>
> I am looking for a procedure that allows selection of variables in a
> clustering attempt.
>
> Specifically I am searching for a way of selecting out noise variables
Hi List,
I am looking for a procedure that allows selection of variables in a clustering
attempt.
Specifically I am searching for a way of selecting out noise variables from a
set of numeric/categorical variables (or of course selecting "non-noise"
variables).
The procedure should work wit
hi there!
i am searching for a possibility to plot the cluster fusion number against the
distance in hierarchical clustering. i used the following code:
distances = dist(my data[, c(1:11)],
method="euclidean")
eward = hclust(distances, method="ward")
plot(eward, labels=my data[, 12], hang=0,cex
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