Hello Mengjie,
I ran viper on a masked dataset (loaded in gene.expression, which is 28392 genes by 2850 cells).
The zero rates hist plot of both genes and cells are in attached. I adjusted the default cutoff value according to the hist plot.
I ran it on both gene.expression and its transpose. However, the first one ran smoothly and saved the output. The second one stopped unexpectedly. It prompts：
Error in imputation_by_samples_posterior_expectation(data, selected_logxx, :
Evaluation error: y is constant; gaussian glmnet fails at standardization step.
The code is written as below:
system.time(res <- VIPER(gene.expression, num = 5000, percentage.cutoff = 0.5, minbool = FALSE, alpha = 0.5, report = TRUE, outdir = outdir, prefix = prefix))
system.time(res <- VIPER(t(gene.expression), num = 5000, percentage.cutoff = 0.88, minbool = FALSE, alpha = 0.5, report = TRUE, outdir = outdir, prefix = prefixt))
zerorateingene.pdf
zerorateincell.pdf
Could you give me a guide to setup the parameter?
best,
jialu
Hello Mengjie,
I ran viper on a masked dataset (loaded in gene.expression, which is 28392 genes by 2850 cells).
The zero rates hist plot of both genes and cells are in attached. I adjusted the default cutoff value according to the hist plot.
I ran it on both gene.expression and its transpose. However, the first one ran smoothly and saved the output. The second one stopped unexpectedly. It prompts：
Error in imputation_by_samples_posterior_expectation(data, selected_logxx, :
Evaluation error: y is constant; gaussian glmnet fails at standardization step.
The code is written as below:
system.time(res <- VIPER(gene.expression, num = 5000, percentage.cutoff = 0.5, minbool = FALSE, alpha = 0.5, report = TRUE, outdir = outdir, prefix = prefix))
system.time(res <- VIPER(t(gene.expression), num = 5000, percentage.cutoff = 0.88, minbool = FALSE, alpha = 0.5, report = TRUE, outdir = outdir, prefix = prefixt))
zerorateingene.pdf
zerorateincell.pdf
Could you give me a guide to setup the parameter?
best,
jialu