Hi everyone,

I am working with data obtained from GEO (NCBI). This data is gene expression found with the Affymetrix Human Genome U133A Array and is analysed to get a log2 from the raw data (fastlo normalized, rma summarized). Could you help me understand what this data is and how I should plot it? I thought that I should just plot it normally, but my PI tells me it is possible that I should put it in a logarithmic scale.

I am trying to look at different genes (7) to find if they are up-regulated or down-regulated in a disease and using actin and TLR4 as max and min expression. Which graph would be best for this and how should I go about this?

Thanks in advance, Lara.

Hi Lara,

It may be a good idea to go through one of the workflows in their entirety. This would help you to better understand the data processing steps that are required for arrays, and also the various ways in which the data can be plot and further analysed for differentially expressed genes.

Please take a look at this popular Bioconductor workflow:

• An end to end workflow for differential gene expression using Affymetrix microarrays (F1000 link)

If you require more specific assistance, then it can help to provide a reproducible example of code and to highlight the points at which you require further assistance. For example, when you say "fastlo normalized, rma summarized", it is not clear what you mean, as RMA (Robust Multiarray Average) is a process that involves a background correction, quantile normalisation, median polish summarisation and log2 transformation. I am unsure at which point the fastlo (fast loess normalization) comes into this?

Kevin