GreenleafLab
Some quesetion about Cluster Identity
Hi，I have some quesetion about Cluster Identity.When using transcriptomic data mapping to identify cell types in scATAC, I have some very confusing cells, This is because I have a large number of samples and a huge number of cells. There is also some overlap between certain cell types. I would like to ask whether I can filter cells based on the mapping scores of predictedGroup_Un. For example, if the score is less than 0.8, I consider that the cell characteristics are not obvious, and I can directly exclude these cells from subsequent analyses.I'd like to ask whether this is reasonable.
Hi @superSXB! Thanks for using ArchR! Lately, it has been very challenging for me to keep up with maintenance of this package and all of my other responsibilities as a PI. I have not been responding to issue posts and I have not been pushing updates to the software. We are actively searching to hire a computational biologist to continue to develop and maintain ArchR and related tools. If you know someone who might be a good fit, please let us know! In the meantime, your issue will likely go without a reply. Most issues with ArchR right not relate to compatibility. Try reverting to R 4.1 and Bioconductor 3.15. Newer versions of Seurat and Matrix also are causing issues. Sorry for not being able to provide active support for this package at this time.
