To Whom it may Concern,

I'm would like to inquire about the appropriate model design in limma for the model below. All patients are healthy, female and lean.

Patient

Tissue

1

Blood

1

Adipose Tissue

1

Buccal Cells

1

Lymph node

2

Blood

2

Adipose Tissue

2

Buccal Cells

2

Lymph Node

3

Blood

3

Adipose Tissue

3

Buccal Cells

3

Lymph Node


We have implemented 2 different ways to implement this: first is simple "pairing" of samples:

design <- model.matrix(~Patient + Tissue)
fit <- lmfit(data, design)

The second treats the data as biological replicates, and uses "Patient" as a blocking variable instead:

design <- model.matrix(~0+Tissue)
corfit <- duplicateCorrelation(data, design, block=Patient)
fit <- lmFit(data, design, block=Patient, correlation=corfit$consensus)

The two different methods give different results. We have read section 8.7 in the limma users guide and are still unsure which method is more appropriate for this particular experimental design. Would you be able to give feedback on this please?

Regards,

Dr. Tim Peters
Postdoctoral Fellow - Bioinformatics and Statistics
CSIRO Mathematics, Informatics and Statistics
Ph: +61 2 9325 3266 | Email: tim.peters@csiro.au
Address: Riverside Life Sciences Centre, 11 Julius Avenue, North Ryde, NSW 2113, Australia


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