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limma dose-response lincs tempO-seq high-throughput transcriptomics

updated 5.7 years ago by Gordon Smyth 47k • written 5.7 years ago by Pekka Kohonen ▴ 190

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Comment: Adjusting for baseline when having longitudinal data, mixed model and no treat by Gordon Smyth 47k

No, you are not losing power. The two possible limma analyses (fixed or random Subject effects) are both more powerful than the alternative…

Comment: Adjusting for baseline when having longitudinal data, mixed model and no treat by Anna ▴ 20

Thanks Gordon Actually, I am working in the clinical statistics department for the last 5 years, even though a bioinformatician, and the "…

Answer: DESeq2 + analysis question for design with uneven time point design by Michael Love 40k

I'd recommend reaching out to a local statistician or someone familiar with linear models in R. Unfortunately, I have to reserve my time on…

Answer: Genes with highest differential expression have very low read counts for most ge by Michael Love 40k

Have you use `lfcShrink`? Or `results` with `lfcThreshold`? Either of these are recommended for prioritizing DE genes.

Comment: Adjusting for baseline when having longitudinal data, mixed model and no treat by Gordon Smyth 47k

> equivqalent in limma would be like a gene by gene specificic design matrix where no BL time point would exist but a continuous variable t…

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A: Ranges from a fasta file

Answer: NA transcript values in my Txdb

Comment: Interpret plot from DiffBind

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