Hi Dr. Johnson, I have one question about multiple covariates in ComBat analysis that bother me for two weeks and I really need your advice. I have a microarray experiment design list below and please look at the *attachment *for details. 1. I ran experiments in 4 different dates in a randomized way, so 4 batches. 2. Each sample has been run with 2 or 3 replicates. 3. 4 parameters(individual, age, status, stage) associate with each sample. None of them is nuisance. Batch is ONLY the effect I want to eliminate. *Analysis I want to do:* I want to perform statistic test to find significant features between groups by status first and then see how they behave on different Individual, stages and ages. I will later select features to distinguish different stages. So I need a method to consider individual, age, status, stage at same times when doing ComBat analysis, so that their biological difference will not be eliminated. *My question is:* What covariates do I need to include? What will be the influence without including them? Can you mention the principle of choosing multiple covariates? Thanks Tiger PS: The bell plot can show batch removed result. But is there a good way to give a quantitative parameter, such as a percent to show how many batch effects have been removed? So we can know how ComBat perform and can convince reviewers? -- Hu Duan (Tiger) Biological Design PhD student Graduate Research Associate Center for Innovation in Medicine The Biodesign Institute, Arizona State University ---------------------------------------------------------------------- ------ ----------- "MY MIND REBELS AT STAGNATION." -- Sherlock Holmes ---------------------------------------------------------------------- ----- ------------ -- Hu Duan (Tiger) Biological Design PhD student Graduate Research Associate Center for Innovation in Medicine The Biodesign Institute, Arizona State University ---------------------------------------------------------------------- ------ ----------- "MY MIND REBELS AT STAGNATION." -- Sherlock Holmes ---------------------------------------------------------------------- ----- ------------

Hey Tiger, See below: On Feb 19, 2013, at 2:16 PM, hu duan wrote: Hi Dr. Johnson, I have one question about multiple covariates in ComBat analysis that bother me for two weeks and I really need your advice. I have a microarray experiment design list below and please look at the attachment for details. 1. I ran experiments in 4 different dates in a randomized way, so 4 batches. 2. Each sample has been run with 2 or 3 replicates. 3. 4 parameters(individual, age, status, stage) associate with each sample. None of them is nuisance. Batch is ONLY the effect I want to eliminate. Analysis I want to do: I want to perform statistic test to find significant features between groups by status first and then see how they behave on different Individual, stages and ages. I will later select features to distinguish different stages. So I need a method to consider individual, age, status, stage at same times when doing ComBat analysis, so that their biological difference will not be eliminated. My question is: What covariates do I need to include? You need to include them all as covariates. Make sure to include age as a numerical covariate. What will be the influence without including them? If your experimental design is balanced across batches, you may not see much of a difference. If there is some unbalance on your design (say there are a higher proportion of treatments in on batch vs another, or if the patients in one batch are younger than in another batch) then you will be removing biological variation with the batch variation. Adding covariates will ensure that the biological variation is untouched by the batch adjustment. Can you mention the principle of choosing multiple covariates? No completely sure what you mean here. Again, you include any covariates of interest so that the biological signal is not removed during the batch adjustment. As far as which covariates to include: anything you variables which you don't want removed from the data. Hope this answers your questions. Thanks Tiger PS: The bell plot can show batch removed result. But is there a good way to give a quantitative parameter, such as a percent to show how many batch effects have been removed? So we can know how ComBat perform and can convince reviewers? -- Hu Duan (Tiger) Biological Design PhD student Graduate Research Associate Center for Innovation in Medicine The Biodesign Institute, Arizona State University ---------------------------------------------------------------------- ----------------- "MY MIND REBELS AT STAGNATION." -- Sherlock Holmes ---------------------------------------------------------------------- ----------------- -- Hu Duan (Tiger) Biological Design PhD student Graduate Research Associate Center for Innovation in Medicine The Biodesign Institute, Arizona State University ---------------------------------------------------------------------- ----------------- "MY MIND REBELS AT STAGNATION." -- Sherlock Holmes ---------------------------------------------------------------------- ----------------- <tiger-design matrix_020613.xlsx=""> [[alternative HTML version deleted]]

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