Re: [R] Methods to explore R data structures

2010-05-28 Thread Timothy Wu
Great, these are valuable tips. Thanks both of you. I appreciate it. :)

Timothy

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[R] Methods to explore R data structures

2010-05-27 Thread Timothy Wu
Hi,

I'm very confused about R structures and the methods to go with them. I'm
using R for microarray analysis with Bioconductors. Suppose without reading
the documentations, what's the best way to explore a data structure when you
know nothing about it?

I am currently using is() / class() to see what the object is. str() /
attributes() to probe inside the object, and someth...@something$something
to walk it and explore. Is there any other way? Also, without reading
documentations, is there a way to know what functions are available to
extract data from it? For example, there is sampleNames() which works on
ExpressionSet and AnnotatedDataFrame (which is a part of ExpressionSet). How
do I know they are available (as sometimes I can't recall where I've seen
them and I forgot the function names). And what are R functions? Are those
two separate functions or polymorphic functions? I'm also pretty confused
about S3, S4, or the regular list. I guess I'm fairly confused about R in
general.

Any good source of reading (hopefully short and understandable, too) would
be appreciated. Thanks.

Timothy

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Re: [R] Methods to explore R data structures

2010-05-27 Thread Martin Morgan
On 05/27/2010 02:13 AM, Timothy Wu wrote:
 Hi,

 I'm very confused about R structures and the methods to go with them.
 I'm using R for microarray analysis with Bioconductors. Suppose
 without reading the documentations, what's the best way to explore a
 data structure when you know nothing about it?

probably by reading the documentation, especially vignettes

  browseVignettes(Biobase)

and then switching to your web browser. If you're asking about
Bioconductor functionality in particular, then the Bioconductor mailing
list is appropriate

  http://bioconductor.org/docs/mailList.html


 I am currently using is() / class() to see what the object is. str()
 / attributes() to probe inside the object, and
 someth...@something$something to walk it and explore. Is there any

This looks at the structure, but many classes will want to be
manipulated by their API.

 other way? . Also, without reading documentations, is there a way to
 know what functions are available to extract data from it? For
 example, there is sampleNames() which works on ExpressionSet and
 AnnotatedDataFrame (which is a part of ExpressionSet). How do I know
 they are available (as sometimes I can't recall where I've seen them
 and I forgot the function names). And what are R functions? Are
 those

For an S4 object 'x', I'd

  class(x)
  getClass(cls)@package

followed by

  showMethods(classes='ExpressionSet',
  where=getNamespace('Biobase'))

or

  cls - c(class(x), getClass(class(x))@contains)
  pkg - getClass(cls)@package
  showMethods(classes=cls, where=getNamespace(pkg))

and conversely

  showMethods(sampleNames, where=getNamespace(pkg))

Methods for S3 classes can be found in a similar way, but using
'methods'. Both of these only discover classes in packages that are
loaded in the currently active session. This will miss plain old
functions that don't declare what type of object they intend to operate
on. If whan you say 'what are the R functions' you're asking for the
function definition, then

  selectMethod(sampleNames, 'ExpressionSet')

 two separate functions or polymorphic functions? I'm also pretty

sampleNames is a generic. There are methods that operate on eSet (a base
class of ExpressionSet), and on AnnotatedDataFrame.

 confused about S3, S4, or the regular list. I guess I'm fairly
 confused about R in general.

For S4

  ?Methods
  ?Classes

For S3, maybe section 10.9 of RShowDoc('R-intro')

Martin


 Any good source of reading (hopefully short and understandable, too)
 would be appreciated. Thanks.

 Timothy

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 __ R-help@r-project.org
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-- 
Martin Morgan
Computational Biology / Fred Hutchinson Cancer Research Center
1100 Fairview Ave. N.
PO Box 19024 Seattle, WA 98109

Location: Arnold Building M1 B861
Phone: (206) 667-2793

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Re: [R] Methods to explore R data structures

2010-05-27 Thread Greg Snow
The TkListView function in the TeachingDemos package is an interactive tool for 
looking at the structure and contents of lists and other objects.

-- 
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.s...@imail.org
801.408.8111


 -Original Message-
 From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-
 project.org] On Behalf Of Timothy Wu
 Sent: Thursday, May 27, 2010 3:14 AM
 To: r-help@r-project.org
 Subject: [R] Methods to explore R data structures
 
 Hi,
 
 I'm very confused about R structures and the methods to go with them.
 I'm
 using R for microarray analysis with Bioconductors. Suppose without
 reading
 the documentations, what's the best way to explore a data structure
 when you
 know nothing about it?
 
 I am currently using is() / class() to see what the object is. str() /
 attributes() to probe inside the object, and
 someth...@something$something
 to walk it and explore. Is there any other way? Also, without reading
 documentations, is there a way to know what functions are available to
 extract data from it? For example, there is sampleNames() which works
 on
 ExpressionSet and AnnotatedDataFrame (which is a part of
 ExpressionSet). How
 do I know they are available (as sometimes I can't recall where I've
 seen
 them and I forgot the function names). And what are R functions? Are
 those
 two separate functions or polymorphic functions? I'm also pretty
 confused
 about S3, S4, or the regular list. I guess I'm fairly confused about R
 in
 general.
 
 Any good source of reading (hopefully short and understandable, too)
 would
 be appreciated. Thanks.
 
 Timothy
 
   [[alternative HTML version deleted]]
 
 __
 R-help@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.

__
R-help@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.