Using multiple factor analysis in edgeR
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Mahnaz Kiani ▴ 20
@mahnaz-kiani-6528
Last seen 7.2 years ago

Hello,

 

I am trying to analyze my data based on section 3.3 of edgeR and I got stuck in the fist part

design <- model.matrix(~0+Group)
 colnames(design) <- levels(Group)
fit <- glmQLFit(y, design)

 

and getting this error :

Error in terms.formula(object, data = data) : object 'y' not found

 

What 'y" stand for?

 

Thanks,

Mahnaz
edger • 1.4k views
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@gordon-smyth
Last seen 3 hours ago
WEHI, Melbourne, Australia

Well, you're not really at the beginning yet. You first have to read your count data into R before you can do any analysis. 'y' represents the DGEList object containing the read counts. See Chapter 2 of the edgeR User's Guide, especially Sections 2.4 and 2.5.

The title of your question says "multiple factor analysis", but you seem to have only one factor.
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Thank you for your answer, I do have different factor, I have two genotypes and 3 sampling from a different part of the plant in each genotype. I want to analyze both genotypes together using factor analysis with a genotype: stage interaction term. I did the analysis before using CLC genomics workbench and that gave me the mean counts number from 3 biological reps, therfore my though was that I can use those mean, instead of putting three count data from each biological reads. Can I do that?

 

Thanks,

Mahanz

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No, you should be using the raw counts from the biological replicates. Otherwise there is no way to model the biological variability if you only have a mean count for every genotype-stage combination.

In any case, your description of the experimental design is not clear. Is "stage" the same as the different part of the plant? Or are the different parts of the plant your "biological replicates"? Were all samples in each group taken from the same plant? Please provide a sample table, like that in Section 3.2.4 of the edgeR user's guide.

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Thnk you, the table that you asked is as follows:

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Mahnaz Kiani ▴ 20
@mahnaz-kiani-6528
Last seen 7.2 years ago
Sample Stem Part Genotype Group Biological rep
1 1 A 1 1
2 1 A 1 2
3 1 A 1 3
4 2 A 2 1
5 2 A 2 2
6 2 A 2 3
7 3 A 3 1
8 3 A 3 2
9 3 A 3 3
10 1 B 4 1
11 1 B 4 2
12 1 B 4 3
13 2 B 5 1
14 2 B 5 2
15 2 B 5 3
16 3 B 6 1
17 3 B 6 2
18 3 B 6 3
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Several points:

  1. Add this information as a comment, rather than adding your own answer. You're not answering your own question.
  2. The interpretation of "Biological rep" is still unclear. For example, do samples 1, 4 and 7 come from the same plant? I assume that 1/4/7 and 10/13/16 come from different plants, given that the genotypes are different.
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That is right, samples 1/4/7 are from different plants, same genotype.

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In that case, you can just make a single factor combining "Stem Part" and "Genotype", e.g., A.1, B.1, and so on, and use a one-way layout such as ~0 + Group as you've done in your original post.

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