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Biotechuos4
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@biotechuos4-13582
Last seen 6.7 years ago
Hi Everyone,
I hope everyone will be doing well.
I'm new in the area of "Microarray gene expression data analysis using R Bioconductor". I want to know about the designing a model.matrix. How to design a model matrix for different types of data like data with two factors (normal, diseased) and also with multiple factors like (normal, disease, time). Can someone please explain, what are the factors to be considered when designing and processing a model matrix for a given study. How to critically understand this issue while working on gene expression data.
Thanking you.
Thank you Aaron Lun.
I'm using a dataset with 12 samples. 6 are normal while 6 are diseased. so How can I design model matrix for it. if I get situation with more than three variables so how to solve that.
I'm looking you expertise as you have answered many of the question well. I have read that and I have done analysis with that. I'm using a sample paper (Research Article) which is already published but the thing is thge DEGs i get are different than the originally reported in that paper.
Read Chapter 9 to see how to handle group-based designs, and Chapter 17 for some case studies. Here's a hint:
If you need to block on other factors, then you can just do:
Thank you very much for your kind response.
Can you please the book name you are talking about #CHapter_9 and 17
It's the limma user's guide.
Thank you brother,
can you please explain a little what do you mean by "block other factors"? it will be of your greatness. and also in the following matrix what about the normal samples. can you a little explain.