[R] Handling missing data

[Martin Morgan]

Vassilis Golfinopoulos wrote:
> Consider this sample dataset (displayed [1:3, 1:3]):
> 
>           T1053B     T1102A      T1129A
> AKT1  -0.02412174  0.1986057          NA
> AURKA -0.37109748 -0.4418542  0.04967051
> BRAF  -0.14589269 -0.1590310 -0.35483226
> 
>> is.na(dataset[1, 3])
> TRUE
> 
> library(impute)
> library(GeneMeta)
> 
> imputed.dataset <- impute.knn(as.matrix(dataset))

impute.knn has a second parameter k with default value 10, the number of
nearest neighbors to use, in gene space, for imputation. For the example
above, there are not 10 nearest neighbors, and unfortunately impute.knn
does not check for this. Is this the case with your real data?

This might address your problem with impute.knn, a GeneMeta example
would help for progress on that front.

Martin

> CRASH!
> 
> 
> 2009/9/21 Greg Snow <Greg.Snow at imail.org>:
>> Help us to help you, show us the code that you tried, what you expected, and what you saw.
>>
>> Does "using NA condition"  mean:
>>
>>> x == NA
>> Which does not work
>>
>> Or
>>
>>> is.na(x)
>> Which should.
>>
>> -----Original Message-----
>> From: "premmad" <mtechprem at gmail.com>
>> To: "r-help at r-project.org" <r-help at r-project.org>
>> Sent: 9/21/09 12:38 AM
>> Subject: [R]  Handling missing data
>>
>>
>> I have to remove missing data both in character and numeric datatype.I tried
>> using NA condition but it is not working ,please help me to solve this.
>> --
>> View this message in context: http://www.nabble.com/Handling-missing-data-tp25530192p25530192.html
>> Sent from the R help mailing list archive at Nabble.com.
>>
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>>
>> ______________________________________________
>> R-help at r-project.org mailing list
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>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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>>
> 
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.