5
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Improve scRNA-seq dataset for further analysis
I don't think you can conclude that the dataset is terrible based on that PCA. Depending on the specific protocol, each scRNA-seq dataset is going to be very different. Unlike bulk RNA-seq where all ...
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5
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Accepted
How to reduce the occupied RAM when you are dealing with a very sparse matrix in a single-cell Experiment in R?
Ah, looks like I can't even procrastinate on StackExchange anymore without seeing work-related stuff. Oh well.
Anyway, the other answers and comments are way off. scran has supported sparse matrices ...
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3
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Accepted
Improve scRNA-seq dataset for further analysis
I usually use a minimum of 200 genes/cell for relaxed filters (500 if possible).
For genes I use presence in at least 10% of the cells.
A few other filters you can try are:
High percentage of reads ...
3
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How to reduce the occupied RAM when you are dealing with a very sparse matrix in a single-cell Experiment in R?
Not a direct solution but some workarounds:
As far as I know, Seurat can work with sparse matrices.
The particular function of ...
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2
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Error in .checkedCall : subset indices out of range
Just posted the question and found out why the error was happening. I had two datasets: raw, and filtered one with half of the rows as raw. I did normalization on the filtered one. Then I calculated <...
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Normalization using parallel R script
The scran::quickCluster method has a BPPARAM (i.e., BiocParallelParam), so if one provides ...
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1
vote
How to reduce the occupied RAM when you are dealing with a very sparse matrix in a single-cell Experiment in R?
Essentially you've hit a RAM bottleneck and the calculation will slow to zero, or in this instance refuse to go forward. The way to do this normally is to parallelize the calculation across the cores ...
M__♦
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AttributeError: module 'scater' has no attribute 'normalize'
I was able to get to the normalized values using logcounts function in the following way:
...
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Improve scRNA-seq dataset for further analysis
Given that this is single-cell sequencing results, you should be using rowSums instead of rowMeans for filtering genes. Most ...
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