get.data: Data Joining, Imputation, and Scaling

In pranavdorbala/proteomicsHF: ARIC Proteomics of Heart Failure -- Biomarker Discovery Pipeline

Description

Data Joining, Imputation, and Scaling

Usage

get.data(master, soma.data, adjust)

Arguments

master	Master study data tibble from haven::read_dta()
soma.data	Parsed SomaLogic proteomic data tibble from get.soma()
adjust	List of Adjustment variables. Must match adjusted.csv files, but should not include id variable.

Value

Tibble of joined and cleaned proteomics and study data.

Examples

## Not run: 
labels <- get.labels('data/proteinMapping.csv', sid,
                     uniprot.full.name,
                     entrezgenesymbol,
                     flag2 == 0)

soma.data.fifth <- get.soma('data/somaV5.txt', labels = labels)

fifth.visit.study <-
  get.adjust(stata = haven::read_dta('data/ARICmaster_121820.dta'),
             mods  = list('data/visit-five/outcomes.csv',
                          'data/visit-five/adjusted.csv'),
             filts = list('data/visit-five/filters.csv'))

adj <- readr::read_csv('data/visit-five/adjusted.csv')[[1]][-1]

visit.data <- get.data(fifth.visit.study, soma.data.fifth, adj)

## End(Not run)

pranavdorbala/proteomicsHF documentation built on March 9, 2021, 12:22 a.m.