Expression data preprocess and normalization
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5.2 years ago
hkarakurt ▴ 150

Hello everyone, I am relatively new in this field and I have different expression data sets from GEO. I am working on downloading them to R, pre-process and analyze. I found many different methods like RMA but I am not sure which one should I use. I want to use a simple method to build a script for all data sets. The simples methods are these: http://jura.wi.mit.edu/bio/education/bioinfo2007/arrays/array_exercises_1R.html (in the middle of page) http://felixfan.github.io/RMA-Normalization-Microarray/

Are those methods enough for normalization and good to use? What other methods do you advice? Should I change my methods depending on my data sets? My datas are all from Illumina HiSeq 2500 platform. I think I should not use Affy package for this. Thank you.

RNA-Seq Bioconductor R GEO GSE • 3.1k views
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You are working with RNA-seq data and looking at methods for microarray data, which is not the same. Have a look at this workflow as your starting point: Bioconductor RNA-seq workflow: gene-level exploratory analysis and differential expression

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Actually I am looking for normalization methods for Illumina HiSeq 2500 expression data. Do platforms change the normalization method?

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Illumina HiSeq 2500 expression data

So, that's RNA-seq, right?

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Yes that's a RNA-seq.

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Then the workflow linked above is okay, for sure for all Illumina RNA-seq, possibly for other short-read sequencers too.

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