Normal cells assigned as aneuploid
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Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 25/100
Research direction
Start with the provided copykat.test call and the use of norm.cell.names for the integrated mouse dataset. Compare the behavior with issue #49 and investigate why healthy cells are assigned as aneuploid; done means identifying a reproducible cause or a clear adjustment to the reported analysis.
Written by the indexing model from the issue text.
Description
Hello,
Many thanks for this tool!
I currently working on a snRNA seq dataset derived from a mouse model for breast cancer.
I have an integrated dataset which contains one normal sample and two cancer samples ( different time points/ tumor progression). So I used this integrated dataset for the copykat by giving in the function all the cells from the healthy sample as the normal cells.
Unfortunately the results are not the best, some healthy cells are assigned as aneuploid.
I was wondering if anyone has any suggestions to go round this issue. I am trying tuning some of the arguments but still I have this problem.
I've read the issue #49 where you are saying that maybe the tumor aneuploidy is weak
I will appreciate any help,
Thanks in advance,
Anna
note: here is the function
copykat.test <- copykat(rawmat=exp.rawdata_snRNA, id.type="S", cell.line="no", ngene.chr=5, win.size=5, KS.cut=0.2,
sam.name="snRNA",norm.cell.names=normal_cell_names, distance="euclidean",genome="mm10",
output.seg=TRUE,plot.genes = TRUE, n.cores=50)
- Dominant language
- R
- Stars
- 305
- Forks
- 66
- PR merge metrics
- No merged PRs in 30d
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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