he example is simple with (A) and (B) only having a few lines. But
in reality, (A) may contain more than 1000 genes and (B) may contain
thousands of interactions.
Any suggestions on how to achieve the above task are welcomed!
--
Suhaila Zainudin
PhD Can
appreciated. TQVM!
--
Suhaila Zainudin
PhD Candidate
Universiti Teknologi Malaysia
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PLEASE do read the posting guide http
ls of Down,
Normal,Up).
I also have provided a self-contained example.
Any comments are highly appreciated.
--
Suhaila Zainudin
PhD Candidate
Universiti Teknologi Malaysia
--
Suhaila Zainudin
PhD Candidate
Universiti Teknologi Malaysia
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levels of -1,0,1).
I also have provided a self-contained example.
Any comments are highly appreciated.
--
Suhaila Zainudin
PhD Candidate
Universiti Teknologi Malaysia
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Thanks for all the reply. I solved the task using apply(as suggested by
Hans).
The tips on S-Poetry and ?Logic are very handy as well.
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ected
output?
2. What are the symbols for OR and AND in R?
Thanks for any feedback
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Suhaila Zainudin
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when
dealing with data of that magnitude?
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PhD Candidate
Universiti Teknologi Malaysia
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Hi,
I have a similar query (how to compare 2 datasets), but my dataset is a bit
different.
I want to compare each data in dataset 1 to data in dataset 2 and get the
data which is common to both datasets.
For example;
I have a a file (named mysample).
V1 V2
YBL064C YBR067C
YBL064C YBR204C
Y
Hi,
Just to inform you that I found the solution for the write.csv task I
mentioned earlier. Searching thru the r-help leads me to this solution..
###Your soln starts
xx <- max(cl2$cl.kmr10.cluster)
# find out how many clusters there are.
my.clusters <- list(NULL) # set up an empty list for st
Hi,
Thanks for your reply. I have tried yr suggestions with success. TQVM.
I have another query, say I want to write each cluster into a csv file such
as follows:
clus1 <- my.clusters[[1]]
write.csv(clus1, file = "clus1.csv")
.
.
clus10 <- my.clusters[[10]]
write.csv(clus10,file = "
cluster number and put the clustered data into separate csv files.
I am trying to run the above step (which is currently done in Excel) in R.
Any comments are appreciated.
--
Suhaila Zainudin
PhD Candidate
Universiti Teknologi Malaysia
--
Suhaila Zainudin
PhD Candidate
Universiti Teknologi
a.frame(wholeset, cl.kmr10$cluster)
After this step, I write cl2 into a csv file and manually partition data
into its respective clusters using Excel.
Then I read the data from each clusters back into R for further analysis.
Can I do the data partitioning directly in R?
TQ
--
Suhaila Zainud
Thanks for the reply Richie.
Finally I tried the following,
> write.csv(mydata.imputed$data, file = "mydata_imputed.csv")
and it worked. I guess I need to refer to the data portion (using $) of the
imputed file.Do correct me if I am wrong, though!
--
Suhaila Zainudin
PhD Candida
Dear all,
I am new to R. I am using the impute package with data contained in csv
file.
I have followed the example in the impute package as follows:
> mydata = read.csv("sample_impute.csv", header = TRUE)
> mydata.expr <- mydata[-1,-(1:2)]
> mydata.imputed <- impute.knn(as.matrix(mydata.expr))
Hi,
I am an R newbie. I am running R2.5.1 on WinXP. I am trying to run a pacakge
(BNArray1.0) that depends on deal 1.2-26 and dynamicGraph 0.2.0.1 . These
are available on http://www.cls.zju.edu.cn/binfo/BNArray/#OLE9 .
I have installed the 3 packages (using local files). When I try to run
BNArra
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