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Answer: Best practice for handling large data (matrix with >2^31-1 non-zero elements) in by Aaron Lun ★ 28k

Consider using a `SVT_SparseMatrix` from the **SparseArray** package, which is explicitly designed for this. **DropletUtils** (in BioC-deve…

Comment: Regarding the issue of background genes in enrichment analysis by zalinkaelisa • 0

Use good features to distinguish the situation of the type of experiment [baseball 9][1] [1]: https://baseball9.io/

Comment: Heatmap of the Count Matrix by gta5movilecom • 0

Using it for the top 20 genes in the heatmap highlights high-expression genes, but may miss out on variance-driven patterns. If you want to…

Answer: Regarding the issue of background genes in enrichment analysis by ATpoint ★ 4.9k

It should imo be the genes that were eligable to yield a "significant" result in your analysis. So, if you test set is derived from differe…

Comment: Applying lmFit(), eBayes() and topTable() for modeling associations between NMR- by Gordon Smyth 52k

> How do these logFC values compare to standard effect sizes derived using a basic regression model like lm()? Exactly the same. Both soft…

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Regarding the issue of background genes in enrichment analysis

Best practice for handling large data (matrix with >2^31-1 non-zero elements) in SingleCellExperiment?

Comment: How can I avoid artifacts in gene set/pathway scoring by UCell and similar algor

Answer: I would like to perform differential expression analysis of lncRNAs using DESeq2

I would like to perform differential expression analysis of lncRNAs using DESeq2 and edgeR.

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