Ding, Yuan Chun
2014-Sep-04 20:10 UTC
[R] calculate Euclidean distances between populations in R with this data structure
I want to calculate Euclidean distance between 12 populations, in each
population there are 20 samples and each sample is measured for 100 genes (these
are microarray data; the numbers here are just examples).
The equation I found is:
distance = sqrt{[sum(Average of xi -average of yi)^2] /n }, i=1 to n;
where xi and yi are the expression of gene i over two populations with p and q
samples (x1, x2,...,xp), (y1, y2,...,yq), n is the number of genes.
part of data are pasted below
row.names pop1.1 pop1.2 pop1.3 pop1.4 pop2.1 pop2.2 pop2.3 pop2.4
7A5 5.38194 4.06191 4.88044 5.60383 6.23101 6.53738 4.80336 5.86136
A1BG 5.15155 4.29441 4.59131 4.90026 4.62908 4.48712 4.73039 4.46208
A1CF 4.22396 4.14451 4.41465 3.93179 4.89638 4.66109 4.20918 4.48107
A26C3 12.1969 12.4179 10.9786 11.7659 11.405 11.7594 11.1757 11.8128
How might one calculate these distances in R with this data structure?
Thanks,
Ding
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Sarah Goslee
2014-Sep-04 23:48 UTC
[R] calculate Euclidean distances between populations in R with this data structure
I'd probably start with ?dist Sarah On Thu, Sep 4, 2014 at 4:10 PM, Ding, Yuan Chun <ycding at coh.org> wrote:> > > > I want to calculate Euclidean distance between 12 populations, in each population there are 20 samples and each sample is measured for 100 genes (these are microarray data; the numbers here are just examples). > The equation I found is: > distance = sqrt{[sum(Average of xi -average of yi)^2] /n }, i=1 to n; > where xi and yi are the expression of gene i over two populations with p and q samples (x1, x2,...,xp), (y1, y2,...,yq), n is the number of genes. > part of data are pasted below > row.names pop1.1 pop1.2 pop1.3 pop1.4 pop2.1 pop2.2 pop2.3 pop2.4 > 7A5 5.38194 4.06191 4.88044 5.60383 6.23101 6.53738 4.80336 5.86136 > A1BG 5.15155 4.29441 4.59131 4.90026 4.62908 4.48712 4.73039 4.46208 > A1CF 4.22396 4.14451 4.41465 3.93179 4.89638 4.66109 4.20918 4.48107 > A26C3 12.1969 12.4179 10.9786 11.7659 11.405 11.7594 11.1757 11.8128 > How might one calculate these distances in R with this data structure? > > > Thanks, > > Ding >-- Sarah Goslee http://www.functionaldiversity.org
David L Carlson
2014-Sep-05 14:42 UTC
[R] calculate Euclidean distances between populations in R with this data structure
There may be a specialized package for this in bioconductor, but it seems that
you could just use aggregate() to calculate the means for each population and
then use the results of that in dist().
?aggregate
-------------------------------------
David L Carlson
Department of Anthropology
Texas A&M University
College Station, TX 77840-4352
-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On Behalf Of Ding, Yuan Chun
Sent: Thursday, September 4, 2014 3:11 PM
To: r-help at R-project.org
Subject: [R] calculate Euclidean distances between populations in R with this
data structure
I want to calculate Euclidean distance between 12 populations, in each
population there are 20 samples and each sample is measured for 100 genes (these
are microarray data; the numbers here are just examples).
The equation I found is:
distance = sqrt{[sum(Average of xi -average of yi)^2] /n }, i=1 to n;
where xi and yi are the expression of gene i over two populations with p and q
samples (x1, x2,...,xp), (y1, y2,...,yq), n is the number of genes.
part of data are pasted below
row.names pop1.1 pop1.2 pop1.3 pop1.4 pop2.1 pop2.2 pop2.3 pop2.4
7A5 5.38194 4.06191 4.88044 5.60383 6.23101 6.53738 4.80336 5.86136
A1BG 5.15155 4.29441 4.59131 4.90026 4.62908 4.48712 4.73039 4.46208
A1CF 4.22396 4.14451 4.41465 3.93179 4.89638 4.66109 4.20918 4.48107
A26C3 12.1969 12.4179 10.9786 11.7659 11.405 11.7594 11.1757 11.8128
How might one calculate these distances in R with this data structure?
Thanks,
Ding
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intended recipient may be able to view the information, forward it to others or
tamper with the information without the knowledge or consent of the sender. If
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received the communication in error, please notify the sender immediately by
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sh to receive further communications via e-mail, please reply to this message
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