Entropy+Analysis+of+QC+Samples+7-20-12

Josh and I were discussing how necessary it is to normalize sample data before calculating the entropy. I argued that the data does not need to be normalized since any shifts in intensity will not affect the spread of the distribution which is what effects the entropy value. Josh said we could test how consistent the entropy values are on the QC samples which should essentially be the same even though there may be some batch differences.

Location of QC Data: S:\Research\labdata\jaricher\QC Data\sera and S:\Research\labdata\jaricher\QC Data\biotin

I'll calculate the entropy of these samples

Results Placed here: L:\storage\CIM Research Folder\DR\2012\7-23-12\qc entropy analysis

Josh also mentioned a possible method of preparing data for normalization using the concept of Bayesian Information Criteria (BIC). From what I remember him saying, this method splits the distribution into groups so in some ways it is kind of like a K means clustering theory.

The entropy of the QC samples can vary drastically between batches over time. Therefore, I may have been incorrect when I previously argued that it is not important to calculate the entropy with normalized data since entropy deals with the spread of intensities rather than degree of the intensities. Calculating the entropy with normalized data may be important to do.

Analysis and graphs can be found here "L:\storage\CIM Research Folder\DR\2012\7-23-12\qc entropy analysis\Entropy of QC Samples.pptx" Original excel sheets here "L:\storage\CIM Research Folder\DR\2012\7-23-12\qc entropy analysis\biotion\Entropy values of biotin samples.xlsx" and here "L:\storage\CIM Research Folder\DR\2012\7-23-12\qc entropy analysis\sera\Entropy values of Sera Samples.xlsx"