Hi,
I have two datasets from HTA platform for which I want to do fRMA normalisation(specifically). As I understand fRMA works with either affybatch object(package affy) or ExpressionFeatureSet(package oligo). How can I do this by using custom cdf file from brain array resource? I have tried using the "hta20hsensgprobe" package from brainarray website and used the following lines of code:
library(oligo) library(hta20hsensgprobe) celFiles<- list.celfiles( "HTA_data",full.names = TRUE) affyRaw <- read.celfiles(celFiles,pkgname="hta20hsensgprobe")
But this gives me the following error:
Error in (function (classes, fdef, mtable) : unable to find an inherited method for function ‘kind’ for signature ‘"probetable"’
The sessionInfo is as follows:
R version 3.1.2 (2014-10-31) Platform: x86_64-apple-darwin10.8.0 (64-bit) locale: [1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8 attached base packages: [1] stats4 parallel stats graphics grDevices utils datasets methods base other attached packages: [1] hta20hsensgprobe_19.0.0 AnnotationDbi_1.28.2 GenomeInfoDb_1.2.4 pd.hta.2.0_3.10.1 RSQLite_1.0.0 DBI_0.3.1 [7] Biostrings_2.34.1 XVector_0.6.0 IRanges_2.0.1 S4Vectors_0.4.0 oligoClasses_1.28.0 frma_1.18.0 [13] Biobase_2.26.0 BiocGenerics_0.12.1 data.table_1.9.4 aroma.light_2.2.1 aroma.affymetrix_2.13.1 aroma.core_2.13.0 [19] R.devices_2.13.0 R.filesets_2.7.1 R.utils_2.0.2 R.oo_1.19.0 oligo_1.30.0 affxparser_1.38.0 [25] R.methodsS3_1.7.0 loaded via a namespace (and not attached): [1] affy_1.44.0 affyio_1.34.0 aroma.apd_0.6.0 base64enc_0.1-3 BiocInstaller_1.16.2 bit_1.1-12 Cairo_1.5-5 [8] chron_2.3-45 codetools_0.2-11 digest_0.6.8 DNAcopy_1.40.0 ff_2.2-13 foreach_1.4.2 GenomicRanges_1.18.4 [15] iterators_1.0.7 magrittr_1.5 MASS_7.3-39 matrixStats_0.14.0 plyr_1.8.2 preprocessCore_1.28.0 PSCBS_0.44.0 [22] R.cache_0.11.0 R.huge_0.9.0 R.rsp_0.20.0 Rcpp_0.11.6 reshape2_1.4.1 splines_3.1.2 stringi_0.4-1 [29] stringr_1.0.0 tools_3.1.2 zlibbioc_1.12.0
Thanks in advance.
Regards,
Sanjana
Hi James,
I am Prathyusha Bachali, working as a Bioinformatician at Ampel Biosolutions. I am working on Hu Gene 1.1 ST arrays. It requires oligo package to analyze rather affy. I am able to do for Affy CDFs. I am trying to use Brainarray CDF too. I created annotation package for Brain array CDF by following the exact instructions mentioned in above reply. I could successfully build the annotation package. How should I get the feature data for the annotation package I created. I could see that rows have been created to featureSet1, but I am not sure how to extract the featureSet1. I tried getNetAffx to get the feature data but it has thrown me an error that getNetAffx cannot be used for GenericFeatureSet. I am wondering how to get the feature data.
Any help would be much appreciated.
Thanks,
Prat
There is no need to make an annotation package yourselves for the remapped/custom/brainarray "CDF" when using
oligo
, because the annotations are already available in the remapped PdInfo object.<<edit: i was not completely correct; as James pointed out below, you still/also need the *.db file, which is also provided by the MBNI group. See his code below. >>
Check this thread (and links) for additional info; especially with respect to the function
annotateEset()
available in the libraryaffycoretools
(function is nowadays available in the 'release' version). A: matching probes to genes from pd.porgene.1.1.st array.There are two problems here. First, you are confusing things; the instructions above are for making a pdInfoPackage, which isn't an annotation package. Instead, it is a package that oligo uses to map probes to probesets so you can summarize your data. Second, you don't need to make these any more, as Manhong Dai is now doing that for you. You can just install the correct pdInfoPackage from MBNI, as well as the annotation package and go from there. As an example, say we wanted to use the Entrez Gene mapped MBNI package. I am on Windows here, so I have to say that the type is 'source'. If you are on linux this isn't necessary, but it will be if you are on MacOS.
And now you can proceed with your analysis.
Dear James, thanks a lot for this answer!