Open wuchx101876 opened 1 year ago
Hi,
Please see the instructions in the user guide. To reproduce the analysis in the paper, you can use the barcodes included in the cell annotations (under /data
in this repo) as --barcodes
input.
In the paper method, "To evaluate CNV detection performance we computed precision and recall based on the extent of overlap between the predicted and true aberrant regions as defined by WGS." I want to know how you deal with the difference of cnv boundary between the Numbat results and WGS results, as well as other tools, for example the infercnv results and WGS results.
@wyt14 Please see this function: https://github.com/kharchenkolab/numbat/blob/32c86a354076af113a3740cbcbc340a9eecc9915/R/utils.R#L2068-L2101 And also this notebook: https://github.com/kharchenkolab/NumbatAnalysis/blob/main/notebooks/benchmark_bulk.ipynb
@wyt14 Please see this function: https://github.com/kharchenkolab/numbat/blob/32c86a354076af113a3740cbcbc340a9eecc9915/R/utils.R#L2068-L2101 And also this notebook: https://github.com/kharchenkolab/NumbatAnalysis/blob/main/notebooks/benchmark_bulk.ipynb
Thanks very much! In the code, how do we obtain the "segs_consensus" dataframe??
I want to know how to get the third parameter "df_allele" when running numbat::run_numbat() function.