Issue with ML.Dev.Prog.Sig Function: About Lasso + survival-SVM

[HeisenbergCai]

Hi,I am currently utilizing the Mime1 package for my bioinformatics research and have encountered an issue with the ML.Dev.Prog.Sig function. Specifically, the following code results in an error:

res <- ML.Dev.Prog.Sig(train_data = list_train_vali_Data$Dataset1, list_train_vali_Data = list_train_vali_Data, unicox.filter.for.candi = T, unicox_p_cutoff = 0.05, candidate_genes = genelist, mode = 'all', nodesize =5, seed = 123)

The error message returned is:

--- 10.Lasso + survival-SVM --- There were 50 or more warnings (use warnings() to see the first 50)

warnings() Warning messages: 1: In snowfall::sfExport("x") : sfExport() writes to global environment in sequential mode.
2: In snowfall::sfExport("time", "status", "maxstepno", "trace", ... : sfExport() writes to global environment in sequential mode.
3: In snowfall::sfExport("time", "status", "maxstepno", "trace", ... : sfExport() writes to global environment in sequential mode.
4: Only deviance, C available as type.measure for Cox models; deviance used instead 5: Only deviance, C available as type.measure for Cox models; deviance used instead 6: In coxph.fit(X, Y, istrat, offset, init, control, weights = weights, ... : Ran out of iterations and did not converge 7: In coxph.fit(X, Y, istrat, offset, init, control, weights = weights, ... : Ran out of iterations and did not converge 8: In coxph.fit(X, Y, istrat, offset, init, control, weights = weights, ... : Ran out of iterations and did not converge 9: In coxph.fit(X, Y, istrat, offset, init, control, weights = weights, ... : Ran out of iterations and did not converge 10: In coxph.fit(X, Y, istrat, offset, init, control, weights = weights, ... : Ran out of iterations and did not converge 11: In coxph.fit(X, Y, istrat, offset, init, control, weights = weights, ... : Ran out of iterations and did not converge 12: In coxph.fit(X, Y, istrat, offset, init, control, weights = weights, ... : Ran out of iterations and did not converge ...... 50: In coxph.fit(X, Y, istrat, offset, init, control, weights = weights, ... : Ran out of iterations and did not converge

How can I solve this problem???

[l-magnificence]

Does the process finish and output the result?

[HeisenbergCai]

Does the process finish and output the result?

Only the results of some of the models are output

[l-magnificence]

I think this may be due to that expression of some genes in your dataset are very low and could not be exactly grouped for coxph analysis like here described (https://stackoverflow.com/questions/52394828/coxph-ran-out-of-iterations-wont-converge-categorical-treatment-continuous)

[HeisenbergCai]

I think this may be due to that expression of some genes in your dataset are very low and could not exactly grouped for coxph analysis like here described (https://stackoverflow.com/questions/52394828/coxph-ran-out-of-iterations-wont-converge-categorical-treatment-continuous)

Thanks for your reply. I`ll try it.