l-magnificence / Mime

Machine learning-based integration model with elegant performance
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error occured when running ML.Corefeature.Prog.Screen #51

Open amell-2022 opened 2 weeks ago

amell-2022 commented 2 weeks ago

library("Mime1")

res.feature.all <- ML.Corefeature.Prog.Screen(InputMatrix = list_train_vali_Data1$Dataset1,

  • candidate_genes = genelist,
  • mode = "all_without_SVM",
  • single_ml = "Lasso",

  • nodesize =5,
  • seed = 5201314 ) [1] "Starting the data preprocess" [1] "Rejecting a null value" [1] "Gets the intersection of genelist and expression profile" [1] "Processing the input representation matrix" [1] "Data preprocessing completed" [1] "Stating the univariable cox regression" 6% 11% 17% 22% 28% 33% 39% 44% 50% 56% 61% 67% 72% 78% 83% 89% 94% 100% [1] "Finished the univariable cox regression" [1] "Starting the data preprocess" [1] "Rejecting a null value" [1] "Gets the intersection of genelist and expression profile" [1] "Processing the input representation matrix" [1] "Data preprocessing completed" [1] "Stating the univariable cox regression" Error in 1:ncol(inputSet[, 4:ncol(inputSet)]) : 参数长度为零 此外: There were 20 warnings (use warnings() to see them)

    i have ensured that the genelist that i put in was included in the train dataset (list_train_vali_Data1$Dataset1): aaaaa <- intersect(genelist,colnames(list_train_vali_Data1[[1]])) identical(aaaaa,genelist) [1] TRUE the dataset1 was established to standard as follows: ID, OS.time, OS, gene_symbols i couldnt figure out the reason that this error occurs, thank you for considering!

l-magnificence commented 2 weeks ago

The error occurs in procesing your dataset2. Please check format of your Dataset2.

amell-2022 commented 1 week ago

i have checked the format of dataset2, just same as dataset1: ID, OS_time, OS,and gene symbols. and the ML.Dev.Prog.Sig just ran well.

aaaaa <- intersect(genelist,colnames(list_train_vali_Data1[[2]])) identical(aaaaa,genelist) [1] TRUE the gene symbols in genelist were included in dataset2. i still couldnt figure it out , looking forward to your reply and thanks