Recent Review / Best practices for (meta) micro array expression data analysis

Question

[William]

Is there something like a recent best practices overview for the (meta)analysis of micro array data anno 2014? With things like data cleanup, normalization, quality control, multiple platforms and larger sets of samples taken into account? And the different analysis you can do in the end, IE Differential Expression or clustering of samples.

Do people still use microarray data a lot in academic commercial research? Or has it mostly been dropped in favor of RNA seq expression analysis?

For DNA mapping / variant calling there is https://www.broadinstitute.org/gatk/guide/best-practices

I am hoping there is something similar for micro array expression analysis but I do suspect it much fuzzier for biological and technical reasons.

Answer 1

[William]

I found this paper a good starting point:

Reuse of public genome-wide gene expression data (Nature Genetics Review 2013)

http://www.nature.com/nrg/journal/v14/n2/execsumm/nrg3394.html

[Mo]

@William Yes people still use it (at least in Europe). there are plenty papers available for example http://www.nature.com/nrg/journal/v7/n1/full/nrg1749.html

Are you searching for review papers or how to analysis one? There is already a post of step by step how to analysis microarray data in R Analysing Microarray Data In Bioconductor