train_pro: Training Data for Prognostic (Survival) Models

Description

A training dataset for prognostic models, containing sample IDs, survival outcomes (time and event status), and gene expression features.

Usage

train_pro

Arguments

Format

A data frame with rows for samples and 31 columns:

sample: character. Unique identifier for each sample.
outcome: integer. The event status, where 1 indicates an event occurred and 0 indicates censoring.
time: numeric. The time to event or censoring.
AC004990.1: numeric. Gene expression level.
AC055854.1: numeric. Gene expression level.
AC084212.1: numeric. Gene expression level.
AC092118.1: numeric. Gene expression level.
AC093515.1: numeric. Gene expression level.
AC104211.1: numeric. Gene expression level.
AC105046.1: numeric. Gene expression level.
AC105219.1: numeric. Gene expression level.
AC110772.2: numeric. Gene expression level.
AC133644.1: numeric. Gene expression level.
AL133467.1: numeric. Gene expression level.
AL391845.2: numeric. Gene expression level.
AL590434.1: numeric. Gene expression level.
AL603840.1: numeric. Gene expression level.
AP000851.2: numeric. Gene expression level.
AP001434.1: numeric. Gene expression level.
C9orf163: numeric. Gene expression level.
FAM153CP: numeric. Gene expression level.
HOTAIR: numeric. Gene expression level.
HYMAI: numeric. Gene expression level.
LINC00165: numeric. Gene expression level.
LINC01028: numeric. Gene expression level.
LINC01152: numeric. Gene expression level.
LINC01497: numeric. Gene expression level.
LINC01614: numeric. Gene expression level.
LINC01929: numeric. Gene expression level.
LINC02408: numeric. Gene expression level.
SIRLNT: numeric. Gene expression level.

Details

This dataset is used to train machine learning models for prognosis. The features are typically gene expression values.