User: mikhael.manurung
mikhael.manurung • 90
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Posts by mikhael.manurung
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... You can transpose the data frame and then save it, like this:
```
tmp <- t(tmp) #transpose data frame
write.csv(tmp, "tmp.csv", row.names = TRUE, col.names = TRUE) # make sure to set row.names to TRUE!
``` ...
written 6 weeks ago by
mikhael.manurung • 90
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... Hi Papyrus,
I also encountered this problem but fortunately, in my dataset, the cell type compositions were not associated with my covariate of interest. If you have the cell type compositions data, why wouldn't you put those together in your formula (meth ~ age.group + cellA + cell B + cell C + a ...
written 6 weeks ago by
mikhael.manurung • 90
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... If it is a csv file then you can use `read.csv`. Good luck! ...
written 6 weeks ago by
mikhael.manurung • 90
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... Note that `list.files` will only, well, list all the files that you have within your working directory. It **DOES NOT** import the data into R. That is why the first thing that you should do is to properly import those data into R. For your data, you can easily use `read.table`.
By the way, it seem ...
written 7 weeks ago by
mikhael.manurung • 90
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... Dear Peter,
Thank you for your prompt response. For `empiricalBayesLM`, would you advise feeding the group variables into the `retainedCovariates` argument?
Best,
Mikhael ...
written 7 weeks ago by
mikhael.manurung • 90
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... Dear all,
I would like to adjust my whole-blood RNA-Seq count data matrix for cell type composition (obtained from hematological analysis & flow cytometry) before doing a coexpression network analysis with `WGCNA`.
So far, I did the following:
```
# I use DESeq2's vst to remove mean-variance ...
written 7 weeks ago by
mikhael.manurung • 90
• updated
7 weeks ago by
Peter Langfelder • 2.1k
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... Did your supervisor elaborate more on the lack of need to normalise your data? Somehow I suspect that your supervisor actually meant that you do not need to transform your count data to something else such as with the `voom` transformation from `limma`.
Anyway, `DGEList` object can be made as such: ...
written 7 weeks ago by
mikhael.manurung • 90
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... I do not think you can use a continuous variable in your design matrix for either ```limma``` or ```edgeR```. Well, you can use it as a covariate for adjustment of confounding or batch effects.
It is possible to correlate the expression of your genes with your continuous predictor, provided you ha ...
written 8 weeks ago by
mikhael.manurung • 90
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... I think the ```maSigPro``` package would be the one that you are looking for. I hope this helps. ...
written 8 weeks ago by
mikhael.manurung • 90
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... ```removeBatchEffect``` should not be used for DE analysis but for other downstream analysis, such as PCA. For adjustment of DE analysis, indeed you should include ```columndata$days``` in design matrix. Therefore, your ```dge``` object should be used. This is important because the linear modeling s ...
written 8 weeks ago by
mikhael.manurung • 90
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