4
votes
Accepted
What trajectory analysis method allows to set the form of the trajectory?
slingshot (Bioconductor) accepts a priori starts and ends. For differential expression along the trajectory you may check tradeSeq.
3
votes
Can 5' end 10x be used instead of 3' end
It depends on the task. If you want to recover TCR and BCR repertoires along with gene expression - 5' is a must. Also, for an overview repertoire analysis you dont even have to perform target ...
2
votes
How to identify a low proportion cell subpopulation in the single-cell RNA-seq data?
Run the usual steps including clustering and visualization via something like UMAP and then color the UMAP by these four markers. That assumes that the surface marker separation you see in flow holds ...
2
votes
Accepted
umap failed to cluster the cells
Without more code and data, this can't be debugged. But first question would be does the data pass basic QC (e.g. look at cellranger web summaries or equivalent). If yes, you could trying different ...
2
votes
how to merge more than two sample in Seurat?
As of 2023 (or Seurat >4 or >3?), simply use merge and write
...
1
vote
Convert ensemble genes to gene names in my sigle cell signature matrix annotated with seurat in R?
I think BioMart will do the gene ID -> gene name conversion you're after:
https://www.ensembl.org/info/data/biomart/index.html
To use BioMart to convert the gene IDs to gene names, you can use the ...
1
vote
Using CSV files continaing scRNA-seq count data from GEO
Please understand that your question is open-ended and essentially you're asking for a complete guidance through your analysis which is not feasible. I recommend to go through either the Seurat ...
1
vote
Accepted
h5ad file format filter
You didn't show us how the original .h5ad object was generated, how you read it in, how you wrote it, and if you did anything else in-between besides filtering. ...
1
vote
h5ad file format filter
Scanpy's h5ad is in fact hdf5 format. This format is used for rapid read/write (i/o) large amounts of data and thats its purpose. Its fairly easy to use from ...

M__♦
- 11.9k
1
vote
How to calculate cell type percentage in every sample
The following package performs this type of analysis and can be directly used on a Seurat object:
paper: propeller: testing for differences in cell type proportions in single cell data
github: Speckle
...
1
vote
How to calculate cell type percentage in every sample
If your cell types and sample names are in separate metadata variables attached to the Seurat object, then you can use table to count up the pairings:
...
1
vote
How to do pathway analysis after scanpy for single cell data after DE analysis?
An easy way to do an enrichment analysis in scanpy is using scanpy.queries.enrich(). This relies on gprofiler, which uses KEGG, GO and other ontologies
1
vote
Accepted
How many percents explained variance by the first 50 principal components of PCA analysis is suitable for downstream `KNN` and `umap`?
Edit To answer the question, you're looking for 80% variance .... from the comments the actual command is np.cumsum which changes things a lot.
Previous response ......

M__♦
- 11.9k
1
vote
Accepted
Best method to compare differentially expressed genes between 2 single cell clusters for GSEA
I wish to focus my contribution singly on ScanPy vs. Seurat FindMarkers.
ScanPy's claim is it is essentially a speeded up version of Seurat FindMarkers with better performance (discussed below) ...

M__♦
- 11.9k
1
vote
Accepted
How to preserve colour assignments in matplotlib when a category is empty?
My recommendation is to report the issue directly on the ScanPy Github page here: https://github.com/scverse/scanpy/issues
This is a shortcoming with the testing of ...

M__♦
- 11.9k
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