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Joyce Gu ▴ 200
@joyce-gu-611
Last seen 10.2 years ago
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
marray marray • 1.5k views
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@jean-yee-hwa-yang-104
Last seen 10.2 years ago
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
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Joyce Gu ▴ 200
@joyce-gu-611
Last seen 10.2 years ago
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
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@jamila-ahdidan-641
Last seen 10.2 years ago
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
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Wenqiong Chen ▴ 120
@wenqiong-chen-652
Last seen 10.2 years ago
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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> 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
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@james-w-macdonald-5106
Last seen 6 hours ago
United States
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 _______________________________________________ Bioconductor mailing list Bioconductor@stat.math.ethz.ch https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
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