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The content of this article mainly focuses on how split_sample.r randomly groups the samples according to the survival data. The content of the article is clear and clear. It is very suitable for beginners to learn and is worth reading. Interested friends can follow the editor to read together. I hope you can get something through this article!

Split_sample.r randomly divides the training set and test set according to the survival data.

Usage: usage: split_sample.r [- h]-I input [- e event] [- t time] [- p propotion] [- o outdir] [- n name] The complete data set is randomly divided into training set and test setoptional arguments:-h,-help show this help message and exit-I input,-- input matrix data [required]-e event -- event event input event list,default: EVENT-t time,-- time time input time list,default:TIME-p propotion,-- propotion propotion input propotion of train set to test set,default:0.6-o outdir,-- outdir outdir output file directory [default cwd]-n name,-- name name output file name prefix [default demo]

Parameter description:

-I input matrix file

Name of the survival event column in the-e file. Default is EVENT.

The name of the time to live column in the-t file. Default is TIME.

-p the ratio of training sets to test sets based on survival data, default is 6:4

-o output file path

-n specify the output file name

Use example: Rscript split_sample.r-I.. / project/zx-20210908-381-TCGA_CHOL/01_meta/survival_time.tsv thank you for reading, I believe you have some understanding of "how split_sample.r randomly groups samples according to survival data", go to practice quickly, if you want to know more related knowledge points, you can follow the website! The editor will continue to bring you better articles!

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