[BioC] Statistics questions regarding the use of Ambion ExFold ERCC standards with Affmetrix ST arrays.

Thornton, Matthew Matthew.Thornton at med.usc.edu
Tue Jan 14 03:47:42 CET 2014


Hello!

I am processing some data collected with GeneChip Mouse Gene 2.0 ST arrays.   I am using the Ambion ExFold ERCC controls (Life Technologies 4456739) These are "spike in" controls consisting of two 'mixes' with the same set of RNA sequences, 92 total, that span 10^6 fold in concentration, furthermore, the difference in concentration between the two 'mixes' is well defined.

I have processed the data using the bioconductor package vsn, using the protocol normalization with "spike-in" controls. I have pulled out the normalized intensities out for the ERCC probes from both groups across my samples 3 treatments and 1 wild-type. When I graph 2 log concentration versus 2 log intensity, I get a sigmoid curve, with a linear region between a 2 log intensity of 6.5 to 10.5. Is it correct to assume that this is the 'dynamic range' of the GeneChip for my experiment? If I have data that is within this range, what would be the most statistically (and scientifically) satisfying statistics that I should obtain (and relate) from the dispersion of the controls to make inference about my data?

Additionally from the data there is an expected fold-change between 'mixes' which can be compared to the fold change obtained from data processing using the average intensity across all samples. In my case what I see is that an expected 2 fold change, is seen as 1.1 fold change. What would be the best way to use this information to make inference?

Is there a forum like Stack Exchange biology or biostars that bioconductor list patrons prefer? The reason why I am asking is I because I have graphs which are easier to post in page rather than in list format.

Any feedback or commentary is greatly appreciated.

Thank you!

Sincerely,

Matt

Matthew E. Thornton

Research Lab Specialist
Saban Research Institute

USC/Children’s Hospital Los Angeles
513X,  Mail Stop 35
4661 W. Sunset Blvd.
Los Angeles, CA 90027-6020

matthew.thornton at med.usc.edu



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