Example: Here's the best overview I've found so far, know any that are better? If not, are there any major issues/gaps in the summary?
Steps in Preprocessing Affymetrix GeneChip Data
Thanks!
Example: Here's the best overview I've found so far, know any that are better? If not, are there any major issues/gaps in the summary?
Steps in Preprocessing Affymetrix GeneChip Data
Thanks!
I think that the overview linked to in the question is reasonable, but incomplete and a little dated. For example, PM/MM is specific to early Affymetrix chips and not much used these days. As David pointed out, summarised differential expression is not the sole outcome of analysis and there are many ways that it can be achieved.
I'd recommend the article A microarray analysis for differential gene expression in the soybean genome using Bioconductor and R. Don't be put off by the reference to soybean; this is a good, general and practical overview of analysis using Bioconductor. After pre-processing, I would also look at some of the methods in Bioconductor that are more recent than the simple "t-test, top 100 list" approach, such as the siggenes package.
The link you provide is quite incomplete and in some instances (e.g. "the end result is always a single expression value for each gene on each chip") misleading. For a more comprehensive overview, I recommend a look at "Bioinformatics and Computational Biology Solutions Using R and Bioconductor" (Robert Gentleman, Vincent J. Carey, Wolfgang Huber, Rafael A. Irizarry and Sandrine Dudoit, Springer). Get it through Amazon or on SpringerLink at http://www.springerlink.com/content/978-0-387-25146-2 . If you just want a recipe for how to run RMA or GCRMA, I recommend the vignettes for those tools which you can find on the bioconductor bioconductor.org) website.
Try this : An (Opinionated) Guide to Microarray Data Analysis by Mark Reimers,
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Mark, i‘’ll reply later.