Hi,
I am using marrayClasses package, read.marrayRaw function to read my
raw data
into R.
I have 89 arrays, I put them in the same directory, and read them all.
but I
got the following error messages,
Error: cannot allocate vector of size 3828 Kb
What is the maximum size marray package can handle to read into R?
Also,I tried to read one file at a time, I got the following messages,
Warning messages:
1: number of items read is not a multiple of the number of columns
2: NAs introduced by coercion
3: NAs introduced by coercion
4: NAs introduced by coercion
5: NAs introduced by coercion
Any suggestion is greatly appreciated!
Thanks
Joyce Gu M.S.
Scientific Programmer
Cancer Genomics Group
Baylor College of Medicine
Phone: 832-824-4680
Fax: 832-825-4038
Hi Joyce,
Are all 89 arrays from the same print-run with with same array layout
information? The object marrayRaw can only handels data from the same
print-run, if you have data from multiple print-run (or print batach)
you
will need to read them into different marrayRaw objects and combined
them
later.
Cheers
Jean
All 89 arrays are from the same print-run with the same array layout
information,I think it is because my computer's RAM is only 256 RAM, I
am in
the processing of upgrade my RAM to 1 Gb now. However, I am able to
read 12
arrays at one time, however, I got the following warnings, maybe that
is why I
got so many NA values.
Warning messages:
1: number of items read is not a multiple of the number of columns
2: NAs introduced by coercion
3: NAs introduced by coercion
4: NAs introduced by coercion
5: NAs introduced by coercion
6: number of items read is not a multiple of the number of columns
7: NAs introduced by coercion
8: NAs introduced by coercion
9: NAs introduced by coercion
10: NAs introduced by coercion
11: number of items read is not a multiple of the number of columns
12: NAs introduced by coercion
13: NAs introduced by coercion
14: NAs introduced by coercion
15: NAs introduced by coercion
16: number of items read is not a multiple of the number of columns
17: NAs introduced by coercion
18: NAs introduced by coercion
19: NAs introduced by coercion
20: NAs introduced by coercion
21: number of items read is not a multiple of the number of columns
22: NAs introduced by coercion
23: NAs introduced by coercion
24: NAs introduced by coercion
25: NAs introduced by coercion
26: number of items read is not a multiple of the number of columns
27: NAs introduced by coercion
28: NAs introduced by coercion
29: NAs introduced by coercion
30: NAs introduced by coercion
31: number of items read is not a multiple of the number of columns
32: NAs introduced by coercion
33: number of rows of result
is not a multiple of vector length (arg 2) in: cbind(Gf,
as.numeric(dat[[name.Gf]]))
34: NAs introduced by coercion
35: number of rows of result
is not a multiple of vector length (arg 2) in: cbind(Gb,
as.numeric(dat[[name.Gb]]))
36: NAs introduced by coercion
37: number of rows of result
is not a multiple of vector length (arg 2) in: cbind(Rf,
as.numeric(dat[[name.Rf]]))
38: NAs introduced by coercion
39: number of rows of result
is not a multiple of vector length (arg 2) in: cbind(Rb,
as.numeric(dat[[name.Rb]]))
40: number of items read is not a multiple of the number of columns
41: NAs introduced by coercion
42: NAs introduced by coercion
43: NAs introduced by coercion
44: NAs introduced by coercion
45: number of items read is not a multiple of the number of columns
46: NAs introduced by coercion
47: number of rows of result
is not a multiple of vector length (arg 2) in: cbind(Gf,
as.numeric(dat[[name.Gf]]))
48: NAs introduced by coercion
49: number of rows of result
is not a multiple of vector length (arg 2) in: cbind(Gb,
as.numeric(dat[[name.Gb]]))
50: NAs introduced by coercion
Could you please give me any suggestion?
Thanks
Joyce
>===== Original Message From Jean Yee Hwa Yang <jean@biostat.ucsf.edu>
=====
>Hi Joyce,
>
>Are all 89 arrays from the same print-run with with same array layout
>information? The object marrayRaw can only handels data from the
same
>print-run, if you have data from multiple print-run (or print batach)
you
>will need to read them into different marrayRaw objects and combined
them
>later.
>
>Cheers
>
>Jean
HI,
I have to normalize some microarray raw data. I don't
know what is best : rma function or the marray
package? For me it seems like the first one does in
one step what the second can do in many steps. I can't
find enough information on the two methods to see
which one to use.
Thanks for your help,
Jamila
Hi,
I have a limma question. I have some proteomic data which I would like
to
analyze using limma and compare the results to that using LPE. What I
have
is a couple of data frames with genes in rows and experiments in
columns,
similar to Affymetrix data like single-channel design. How can I plug
in
these data into available functions in limma to do the analysis. Maybe
I
have missed something but looks like limma only takes eset from Affy
data?
Can I directly replace eset with my data.frame in when calling lmFit
function?
Thanks,
wenqiong
> Hi,
> I have a limma question. I have some proteomic data which I would
like
> to analyze using limma and compare the results to that using LPE.
What I
> have is a couple of data frames with genes in rows and experiments
in
> columns, similar to Affymetrix data like single-channel design. How
can
> I plug in these data into available functions in limma to do the
> analysis. Maybe I have missed something but looks like limma only
takes
> eset from Affy data? Can I directly replace eset with my data.frame
in
> when calling lmFit function?
The function lmFit() accepts any sort of input for the expression
information: matrix, data.frame, exprSet etc.
Gordon
> Thanks,
> wenqiong
Wenqiong,
limma is quite adept at determining what you are using and taking the
correct actions. For instance, the help for lmFit has this to say
about
what sort of data object you can pass to lmFit:
object: object of class 'numeric', 'matrix', 'MAList', 'marrayNorm'
or 'exprSet' containing log-ratios or log-values of
expression for a series of microarrays
So you should be able to pass your data after coercing to a matrix.
HTH,
Jim
James W. MacDonald
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
7410 CCGC
Ann Arbor MI 48109
734-647-5623
>>> "Wenqiong Chen" <wenchen@diversa.com> 02/26/04 08:01PM >>>
Hi,
I have a limma question. I have some proteomic data which I would like
to
analyze using limma and compare the results to that using LPE. What I
have
is a couple of data frames with genes in rows and experiments in
columns,
similar to Affymetrix data like single-channel design. How can I plug
in
these data into available functions in limma to do the analysis. Maybe
I
have missed something but looks like limma only takes eset from Affy
data?
Can I directly replace eset with my data.frame in when calling lmFit
function?
Thanks,
wenqiong
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