User: Angelos Armen

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Posts by Angelos Armen

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Comment: C: Feature selection across batches in simpleSingleCell when spike-ins are not avai
... In the [merging vignette][1] of `compareSingleCell`, `var.tech` is computed by `combineVar` within `multiBlockVar`. `combineVar`, however, returns mean variances across batches. Shouldn't [pooled variances][2] be returned instead? [1]: https://github.com/MarioniLab/compareSingleCell/blob/master/ ...
written 1 day ago by Angelos Armen • 0
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Comment: C: Feature selection across batches in simpleSingleCell when spike-ins are not avai
... > Is it? Looks like it's being called with universe. Sorry my bad, you're right. ...
written 3 days ago by Angelos Armen • 0
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Comment: C: Feature selection across batches in simpleSingleCell when spike-ins are not avai
... > multiBatchNorm() is called on the universe of all common genes, not just the HVGs. This is actually important to reduce the risk of violating the non-DE assumption between batches. Sorry I meant to write > genes with positive biological variance in any batch should be selected before calli ...
written 3 days ago by Angelos Armen • 0
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Feature selection across batches in simpleSingleCell when spike-ins are not available.
... In the `simpleSingleCell` *Correcting batch effects* [vignette][1] spike-ins are available. What is the recommended workflow in the absence of spike-ins? I understand that `makeTechTrend` should be applied to each batch separately and then genes with positive biological variance in any batch should ...
simplesinglecell written 4 days ago by Angelos Armen • 0 • updated 4 days ago by Aaron Lun • 24k
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Feature selection across batches in simpleSingleCell "Correcting batch effects" vignette
... In the *Feature selection across batches* section of the `simpleSingleCell` *Correcting batch effects* [vignette][1], genes with positive average (across batches) biological variance are selected. What is the reasoning behind that? Why aren't genes with positive biological variance in any batch sele ...
simplesinglecell written 4 days ago by Angelos Armen • 0 • updated 4 days ago by Aaron Lun • 24k
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Comment: C: k argument in buildSNNGraph
... > If you have a subpopulation with fewer than k+1 cells, buildSNNGraph() will forcibly construct edges between cells in that subpopulation and cells in other subpopulations. This increases the risk that the subpopulation will not form its own cluster as it is more interconnected with the rest of ...
written 4 days ago by Angelos Armen • 0
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k argument in buildSNNGraph
... In the documentation of buildSNNGraph it says that > The choice of k can be roughly interpreted as the minimum cluster size. Can I have an explanation for this please. ...
scran written 13 days ago by Angelos Armen • 0 • updated 12 days ago by Aaron Lun • 24k
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Comment: C: Preprocessing in scran::doubletCells
... Yes that makes sense. I was thinking of cell hashing used merely to multiplex samples from different donors and/or conditions. In that case, inter-sample and intra-sample doublets would form separate clusters (as cells would cluster by sample) and your strategy wouldn't be applicable. To take full a ...
written 13 days ago by Angelos Armen • 0
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Comment: C: Preprocessing in scran::doubletCells
... Thank you for the detailed reply Aaron. The problem with cell hashing and multiplexed genotypes is that they can only detect inter-sample doublets; intra-sample doublets go undetected. Therefore computational approaches are still needed. ...
written 17 days ago by Angelos Armen • 0
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Preprocessing in scran::doubletCells
... Hi, In the [Detecting doublets in single-cell RNA-seq data][1] vignette, scran::computeSumFactors and scran::denoisePCA are used to compute size factors and choose the number of PCs, respectively, before using scran::doubletCluster to detect doublet clusters. However scran::doubletCells is called w ...
scran simplesinglecell written 19 days ago by Angelos Armen • 0 • updated 19 days ago by Aaron Lun • 24k

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