User: eleonoregravier

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France
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Posts by eleonoregravier

<prev • 23 results • page 1 of 3 • next >
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Comment: C: Batch with only one sample or condition
... I understand what you say for batches 5 and 6 but for the other batches (batch 2 and 3 for example), there is not necessary the 2 samples from the same patient in the same batch... so not take into account batch effect is not correct because differences within a patient can be due to batch effect.   ...
written 23 months ago by eleonoregravier40
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Comment: C: Batch with only one sample or condition
... Hi again, The last samples (batches B5 and B6) are not yet processed in spectrometry. I think it would be possible to ask for processing again some of the samples already processed in batches B1 to B4 within the batches B5 and B6. It could simply "save" these samples but I am wondering if it could ...
written 23 months ago by eleonoregravier40 • updated 23 months ago by Gordon Smyth32k
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Comment: C: Batch with only one sample or condition
... Thanks al lot Gordon and Aaron for your valued help Eléonore ...
written 23 months ago by eleonoregravier40
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Comment: C: Batch with only one sample or condition
... Dear Aaron and svlachavas, Thanks for your quick answers. If I well understand, Aaron recommends to use the two following approaches and see what happens : design <- model.matrix(~0+batch+Treat) and patient in duplicateCorrelation design <- model.matrix(~0+Treat) and batch in duplicateCorr ...
written 23 months ago by eleonoregravier40 • updated 23 months ago by Ryan C. Thompson6.1k
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Batch with only one sample or condition
... Hi BioC community, I have proteomic data for 2 conditions A and B. 15 patients are included in A group and 40 patients in B group. The proteome of each patient was measured at time 0 (before treatment) and time 22 (after treatment). So we study 110 samples, corresponding to 55 patients (2 samples b ...
limma batch effect written 23 months ago by eleonoregravier40 • updated 23 months ago by Gordon Smyth32k
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Comment: C: limma with continous covariate depending on gene, 2 block variables, pairing and
... Yes, it will safer ! ...
written 24 months ago by eleonoregravier40
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Comment: C: limma with continous covariate depending on gene, 2 block variables, pairing and
... OK for T1. Are you OK with my computation of treatment effect and sequence effect in the previous comment ? Thank very much for having spent time on my problem Eleonore   ...
written 24 months ago by eleonoregravier40
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Comment: C: limma with continous covariate depending on gene, 2 block variables, pairing and
... Hi Aaron, Thanks again for your help. I understand the part with gp.site where the reference level is T1 to explain evolution in different combinations treatment/time/site. For example treatment effect can be computed by substracting the mean from all the "NT" coefficients (4 terms) to the mean from ...
written 24 months ago by eleonoregravier40
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Comment: C: limma with continous covariate depending on gene, 2 block variables, pairing and
... Hi Aaron and thanks again for your comments. I think I was not very clear to ask my questions, that’s why here are more details : I very well understand that the 8 last coefficients represent evolution relatively to T1. In our “clinical” model, we ALSO (in addition to explain the evolution) inc ...
written 24 months ago by eleonoregravier40
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Comment: C: limma with continous covariate depending on gene, 2 block variables, pairing and
... Thank you very much Aaron. Here is my script, coud you please check if it is correct ? Moreover, I also have some questions, if could answer it would be great : I guess from what you have written that the interpretation of the coefficients is: Intercept : log average expression of P101 in T ...
written 2.0 years ago by eleonoregravier40

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Popular Question 8 months ago, created a question with more than 1,000 views. For batch effect : comBat or blocking in limma ?

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