Ina discussed how we can apply hypothesis testing to the gene expression data from microarrays. We got to know difference in Z-statistic formula when applied to observations directly versus the mean of observations (which follows the Normal Distribution according to the Central Limit theorem). The rest of the chapter on Hypothesis Testing will be studied individually and an overview of tests will be discussed on Wednesday, when they are applied, how they are applied and differences between tests conducted in same scenarios.
References :
1. X. Cui, G. A. Churchill, "Statistical tests for differential expression in cDNA microarray experiments", (Review), Genome Biology 2003, 4:210.
2. J. A. C. Sterne, G. D. Smith, "Sifting the evidence - what's wrong with significance tests?", (Education and Debate)BMJ, 27 January 2001, Volume 322.
Showing posts with label normal distribution. Show all posts
Showing posts with label normal distribution. Show all posts
Monday, September 15, 2008
Thursday, September 4, 2008
Meeting Summary for 9/3/08
We worked through chapter 3 of the Montgomery book and talked about various statistical distributions, i.e. normal, lognormal, gamma, poisson, etc. We also tried to relate them to our area of study, which is elaborated by Archana's post earlier.
For next time we decided to discuss data pre-processing for DNA microarrays. I have a few books on my desk, one by Knudsen, one by Draghici, and one by Speed that could lend some insight. Archana already addressed the other goal of assumption of normal distribution of such data. Next time Archana should also brief us on use of the binomial distribution as it pertains to enrichment of gene ontology terms. We all decided to independently investigate when and where the gamma distribution is used in biology besides the one place we knew already, namely as a step in getting the beta distribution for discrete Bayesian network analysis.
Wednesday, September 3, 2008
Microarray Data- Normally Distributed ?
I applied the normality tests on the microarray data (expression values for one gene) and it looks like it is NOT normally distributed contrary to our discussion.
The tests are Andersen-Darling & Kolmogorov-Smirnov. Here are the histograms and test results :
Labels:
andersen-darling,
KS-test,
normal distribution
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