Model is empty!

[Kai6662]

When I tried to use my own data, I got the bug information. I tested using the sample data, it worked. But my data was failed to run.

fit <- bseqsc_proportions(bulk, B, verbose = TRUE)

• Data features: 'TSPAN6', 'TNMD', ..., 'AC022726.2' (53,145 total)
• Basis features: 'GZMA', 'NKG7', ..., 'MYH11' (37 total)
• Common features: 'CD79B', 'CD22', ..., 'LTB' (37 total)
• Converting to linear scale
• Writing input files ... OK

• Running CIBERSORT ... Show Traceback

  Rerun with Debug Error in predict.svm(ret, xhold, decision.values = TRUE) : Model is empty!

Traceback: 12. stop("Model is empty!") 11. predict.svm(ret, xhold, decision.values = TRUE) 10. predict(ret, xhold, decision.values = TRUE) 9. na.action(predict(ret, xhold, decision.values = TRUE)) 8. svm.default(X, y, type = "nu-regression", kernel = "linear", nu = nus, scale = F) 7. svm(X, y, type = "nu-regression", kernel = "linear", nu = nus, scale = F) at CIBERSORT.R#58 6. FUN(X[[i]], ...) 5. lapply(X, FUN, ...) 4. mclapply(1:svn_itor, res, mc.cores = 1) at CIBERSORT.R#62 3. CoreAlg(X, y, absolute, abs_method) at CIBERSORT.R#200 2. CIBERSORT(xf, yf, ...) 1. bseqsc_proportions(bulk, B, verbose = TRUE)

[josemss]

When I tried your tutorial, with your own data, I get the error:

fit <- bseqsc_proportions(eset, B, verbose = TRUE) Error in predict.svm(ret, xhold, decision.values = TRUE) : Model is empty!

Traceback:

16: stop("Model is empty!") 15: predict.svm(ret, xhold, decision.values = TRUE) 14: predict(ret, xhold, decision.values = TRUE) 13: na.action(predict(ret, xhold, decision.values = TRUE)) 12: svm.default(X, y, type = "nu-regression", kernel = "linear", nu = nus, scale = F) 11: svm(X, y, type = "nu-regression", kernel = "linear", nu = nus, scale = F) at CIBERSORT.R#103 10: FUN(X[[i]], ...) 9: lapply(1:svn_itor, res) at CIBERSORT.R#109 8: CoreAlg(X, y, absolute, abs_method) at CIBERSORT.R#247 7: CIBERSORT(sig_matrix = x, mixture_file = y) at CIBERSORT.R#289 6: eval(ei, envir) 5: eval(ei, envir) 4: withVisible(eval(ei, envir)) 3: source(cib, local = env) 2: bseqsc_config(error = TRUE) 1: bseqsc_proportions(eset, B, verbose = TRUE)

Thanks.

[BirongZhang]

Hi all,

I got the same error:

> results <-cibersort(sig_matrix, mixture_file, perm=50, QN=TRUE)
Error in predict.svm(ret, xhold, decision.values = TRUE) : 
  Model is empty!

> traceback()
12: stop(condition)
11: signalConditions(obj, exclude = getOption("future.relay.immediate", 
        "immediateCondition"), resignal = resignal, ...)
10: signalConditionsASAP(obj, resignal = FALSE, pos = ii)
9: resolve.list(y, result = TRUE, stdout = stdout, signal = signal, 
       force = TRUE)
8: resolve(y, result = TRUE, stdout = stdout, signal = signal, force = TRUE)
7: value.list(futures)
6: future::value(futures)
5: furrr_template(args = x, fn = fn, dots = dots, n = n, options = options, 
       progress = progress, type = type, map_fn = map_fn, names = names, 
       env_globals = env_globals, expr = expr, extract = furrr_map_extract)
4: furrr_map_template(x = .x, fn = .f, dots = list(...), options = .options, 
       progress = .progress, type = "list", map_fn = purrr::map, 
       env_globals = .env_globals)
3: future_map(1:svn_itor, res)
2: CoreAlg(X, y)
1: cibersort(sig_matrix, mixture_file, perm = 50, QN = TRUE)

here is LM22.txt:

Here is my mixture file:

Any advice would be appreciated, thanks!

[zpingfeng]

https://github.com/shenorrLabTRDF/bseqsc/issues/11#issuecomment-982806065 I got similar error when I run cibersort with some of my own data. Now I figured our the problem is that the labels of geneID are slightly different. It works after I fixed the labels