Closed pigyun906 closed 1 year ago
Hi @pigyun906 Seems there is a larger expression variation in your data. Please can you loosen cutoff_normal_range and cutoff_tumor_range to large values, for example cutoff_normal_range = c(0, 2.0), cutoff_tumor_range = c(0, 2.8)? You can visualize the expression variation in the tumor and normal samples using the function plot_sd, which is included in the DeMixT_preprocessing.R script: plot_sd(PRAD, label) and adjust the two cutoffs. Thanks.
It works smoothly. Thanks.
Hi, thank you for developing a nice tool
I followed the DeMixT tutorial to get TmS value described here (Estimation of tumor cell total mRNA expression in 15 cancer types predicts disease progression). But, I got an error not generating a matrix in DeMixT_preprocessing(). Maybe my raw count matrix consists of ~26000 genes, and you selected first ~9000 genes of about 50000 genes as followed GDC mRNA Analysis Pipeline. So, your selection criteria is too harsh for me. In this case, should I get ~50000 total count matrix? or how to apply it to my raw count data (~26000)?
Thank you.