Very basic question, where to start? - (Oct/29/2014 )

Hello, 

I hope everyone is doing well. I have moved to the US six months ago to start a grad school next year. I volunteered in one of the labs of the cancer center at the university I look to enroll at its program. I'm well trained in bench work which makes everyone pleased with my experiments conducting but I'm terrible at data. I know nothing about data, I just started a free course that was presented by Stanford called ( Statistics in Medicine) but I need someone to guide me to more introductory books and subjects that would help me to interpret data. I refer to it as data without specification because it's really gibberish to me, we do gene expression and I find myself lost when looking at heat maps, they keep talking talking about R program, regression and and a lot of terms that leave me clueless. I'm very embarrassed to ask anyone about that in person since it's basics for US students as well as most of international students but not for me.  

Please advise me where to start. This forum is great. The last time I've been here I was able to learn a lot of things about Flow Cytometry which helped to understand and do sorting and FACS and so on. 

Thanks 

Gene expression is a tricky topic because the analysis is quite complicated. As far as I know there aren't a lot of basic guides around, but a good place to start would be the NCBI bookshelf. Exactly how you do the analysis is dependent on the method that you are using, as you talk about heatmaps you are probably doing microarray or possibly next generation sequencing.

For a basic statistics guide, the user guide for the GraphPad Prism software is quite good, but it won't deal with gene expression analysis.

Heat maps are a graphical representation of the fold change (how much a gene has been up or down regulated, 2 fold is double the normal expression), between control and experimental. Usually these have a representation of red and green, but you could use any colours you want, with one colour representing the highest positive fold change (upregulated), shading through to the highest negative fold change (downregulated). a good basic piece of software for this is MeV (free too)

Regression is a method of working out correlations between things.

R is an extremely powerful statistical analysis program capable of handling large datasets (you need this when doing gene expression analysis), which is a failing of most other statistical programs (try filling all rows of a couple of columns in Excel for example, and then doing some analysis). Unfortunately it is a tricky program to learn as you usually need to use command line (i.e. typed commands) to get it to do what you want. if you want a GUI for R try RKWard

Thank you Bob1, I very much appreciate your response.