teng-gao
commented
7 months ago Hello,
segs_loh option is meant for very pure tumors (almost no normal cells) that have clonal deletions in certain regions, which can be excluded using segs_loh in order to more accurately find the diploid baseline.
If you want to remove CNVs that have weak support you can adjust min_LLR or max_entropy. See https://kharchenkolab.github.io/numbat/reference/run_numbat.html
hanjun98
Hi, I have a quetion about removing cnv like noise
First, I use Run_numbat(function) with option like this
out = run_numbat( count_mat, # gene x cell integer UMI count matrix ref_hca, # reference expression profile, a gene x cell type normalized expression level matrix df_allele, # allele dataframe generated by pileup_and_phase script genome = "hg38", t = 1e-5, ncores = 5, plot = TRUE, out_dir = paste0('/mnt/gmi-l1/_90.User_Data/dhthxkr/MDS/',sample,'/Numbat') )And then, I got this result(panel_2.png)
but, I think CNV in chr12 is noise, so I wanna remove them, and then use Run_numbat(function) with segs_loh Because Your documentation explain that segs_loh: dataframe Segments of clonal LOH to be excluded, so I think this option make them to remove noise.
out = run_numbat( count_mat, # gene x cell integer UMI count matrix ref_hca, # reference expression profile, a gene x cell type normalized expression level matrix df_allele, # allele dataframe generated by pileup_and_phase script genome = "hg38", t = 1e-5, ncores = 10, plot = TRUE, segs_loh = segs_loh, out_dir = paste0('/mnt/gmi-l1/_90.User_Data/dhthxkr/MDS/',sample,'/Numbat_v2') )But, I got this result(panel_2.png).
It have little bit changes, but still have CNV in chr12. so I'm curious how to remove CNV like noise and why couldn't remove CNV in chr12, when I use segs_loh(option)
Thank you for reading