Package with useful functions for the MSc HDA&ML Translational Data Sciences and Computational Epidemiology projects
Functions built by March 31st:
quantile_check()--> mostly internal use
Analysis(): performs cross-validation for any given model and given dataset or combination of datasets
Install in your machine (from RStudio): Note: the imperial HPC RStudio session cannot install xgboost which is a dependency of this package, so do not try to install this package from the HPC RStudio.
library(devtools) library(dplyr) devtools::install_github("lc5415/HDATDS") library(HDATDS)
Install in your machine (Terminal): I would recommend installing this package in a new environment given dependecy issues may arise otherwise.
conda create --name NewProjectEnv conda activate NewProjectEnv conda install -c lucha6 r-hdatds
# Original biomarker dataframe data("bio.example") data("cov") # Load biomarkers and covariates data frames (bio and cov) and merge them by ID bio = merge(bio.example, cov[,c("ID","age_cl","gender")], by = "ID") ids = bio$ID # keeping explicit copy of IDs rownames(bio) = bio[,1] # assuming ID is the first column bio = bio[,-1] bio$age_cl = as.factor(bio$age_cl) bio$gender = as.factor(bio$gender) bio = bio[complete.cases(bio), ] #function does not handle NAs internally # Run BHS calculation using paper reference scores_paper = BHSCalculator(bio, "Paper", stratified = TRUE, bySystems = TRUE)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.