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hemberg-lab / scmap

A tool for unsupervised projection of single cell RNA-seq data
http://bioconductor.org/packages/scmap
GNU General Public License v3.0
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Poor self-mapping with SMART-seq data #18

Open a-solovyev12 opened 4 years ago

a-solovyev12 commented 4 years ago

Hello,

Thank you for developing scmap.

I was running a self-projection of Tabula Muris dataset to test the method and found that on the SMART-seq version of the dataset the proportion of 'unassigned' cells is very high - up to 50%. This is apparently caused by similarity metrics falling below the specified threshold. The same analysis on the Tabula Muris UMI-based dataset yields much higher assignment rate, over 90% (data from this publication: https://doi.org/10.1186/s13059-019-1795-z). I was wondering what could be a reason for this difference between technologies? Any suggestions would be appreciated.

mhemberg commented 4 years ago

Hi,

and thanks for your comments. I am not entirely sure why this happens. The best advice we have for the situation when there are many unassigned is to lower the threshold parameter from the default value of .7.