Go Back   SEQanswers > Bioinformatics > Bioinformatics

Similar Threads
Thread Thread Starter Forum Replies Last Post
micro array HAllen Bioinformatics 0 07-18-2015 10:26 PM
Micro Array/RNAseq sets from serous/mucous gland sindrle Bioinformatics 2 05-08-2014 05:45 PM
USA : Bioinformatics Analyst Position in Next-Generation Sequencing/ Micro-Array Serv ladin Academic/Non-Profit Jobs 0 07-19-2012 07:28 AM
PubMed: The use of ultra-dense array CGH analysis for the discovery of micro-copy num Newsbot! Literature Watch 0 01-29-2011 10:50 AM

Thread Tools
Old 04-03-2018, 06:35 AM   #1
Senior Member
Location: USA

Join Date: Nov 2013
Posts: 182
Default Micro-array: Huex 1st v2


This is first time I'm dealing with Micro-array data. I've affymetrix human exon arrays. Cases and control in total are 223.
I tried few things but kind of lost in between.

I perform rma at probe level and at core level. But the output matrix is same in both the cases is same.
22,000 rows (one per probe) and column count is 223. I'm unable to understand why is that and how?

celFiles <- list.celfiles("../CEL")
rawData <- read.celfiles(celFiles)

geneSummaries <- rma(rawData)
write.table(getexpression_core, "PD_RMAnormalized.txt")
Core level:
celFiles <- list.celfiles("../CEL")
rawData <- read.celfiles(celFiles)

geneSummaries <- rma(rawData, target="core")
write.table(getexpression_core, "PD_RMAnormalized_core.txt")
Dimensions for PD_RMAnormalized.txt and PD_RMAnormalized_core.txt are same.

I'm assming that RMA by default normalizes at probe level.

?rma doesn't show me what's the default method it applies.

other attached packages:
[1] DBI_0.8 RSQLite_2.1.0
[4] ff_2.2-13 bit_1.1-12 oligo_1.42.0
[7] Biostrings_2.46.0 XVector_0.18.0 IRanges_2.12.0
[10] S4Vectors_0.16.0 Biobase_2.38.0 oligoClasses_1.40.0
[13] BiocGenerics_0.24.0 dplyr_0.7.4 stringr_1.3.0

loaded via a namespace (and not attached):
[1] Rcpp_0.12.16 BiocInstaller_1.28.0
[3] pillar_1.2.1 compiler_3.4.2
[5] GenomeInfoDb_1.14.0 bindr_0.1.1
[7] bitops_1.0-6 iterators_1.0.9
[9] tools_3.4.2 zlibbioc_1.24.0
[11] digest_0.6.15 memoise_1.1.0
[13] preprocessCore_1.40.0 tibble_1.4.2
[15] lattice_0.20-35 pkgconfig_2.0.1
[17] rlang_0.2.0 Matrix_1.2-12
[19] foreach_1.4.4 DelayedArray_0.4.1
[21] bindrcpp_0.2.2 GenomeInfoDbData_1.0.0
[23] affxparser_1.50.0 bit64_0.9-7
[25] grid_3.4.2 glue_1.2.0
[27] R6_2.2.2 blob_1.1.1
[29] magrittr_1.5 splines_3.4.2
[31] codetools_0.2-15 matrixStats_0.53.1
[33] GenomicRanges_1.30.3 assertthat_0.2.0
[35] SummarizedExperiment_1.8.1 stringi_1.1.7
[37] RCurl_1.95-4.10 affyio_1.48.0
Bioinformaticscally calm
bio_informatics is offline   Reply With Quote


Thread Tools

Posting Rules
You may not post new threads
You may not post replies
You may not post attachments
You may not edit your posts

BB code is On
Smilies are On
[IMG] code is On
HTML code is Off

All times are GMT -8. The time now is 06:32 PM.

Powered by vBulletin® Version 3.8.9
Copyright ©2000 - 2018, vBulletin Solutions, Inc.
Single Sign On provided by vBSSO