raw_data/description.md

Data processing mimics Buergel et. al, Nat Med 2022 (https://www.nature.com/articles/s41591-022-01980-3)

All detail for endpoints, covariates, metabolites can be viewed in 
https://docs.google.com/spreadsheets/d/1XqFFPq3HC2j1hydRc2rUG-SaEXtChmdjcXrJ3XU87To/edit?usp=sharing

1. Endpoints/Outcome
   Binary outcome: /proj/yunligrp/users/djw/UKB_multiomics/rep_NM/ICD10_time_to_event.tab (***)
   Generated from ICD10 code, including f.eid, date of birth, sex, age at death, baseline visit, censor time, death date,
   24 clinical endpoint status (binary), and corresponding event time. See detail for 24 endpoints in google sheets above.
   Survival residual outcome: /proj/yunligrp/users/djw/UKB_multiomics/rep_NM/surv_res_phase2/surv_res_*.tab (***)
   survival residuals are obtained by adjusting three different covariates sets: age+sex, ASCVD (8 CVD related predictors) and PANEL (20 comprehensive predictors). Suffix "_overlap" means only include patients with full record of both metabolomics and proteomics (sample size ~22k), suffix "_all" represents the patients with full metabolomics data (sample size ~277k)

1. Covariates
   Original file: /proj/yunligrp/users/djw/UKB_multiomics/rep_NM/final.predictors.tab
   imputed by MICE: /proj/yunligrp/users/djw/UKB_multiomics/rep_NM/covariates_imp_new.tab (***)
   included 40 covariates (see covariates detail in google sheets). 
   The imputed version only include individuals with either metabolites record or proteomics

2. Metabolites
   Original file: /proj/yunligrp/users/altapia/UKB_MWAS/ukb_metabofilter_complete_eur.txt
   NatMed including 161 metabolites (see them in google sheets).
   We have 159 available metabolites in phase 2 data, sample size ~ 277k: 
   /proj/yunligrp/users/djw/UKB_multiomics/rep_NM/metabolites_phase2_keep.tab (***)

3. proteomics
   A raw data: /proj/yunligrp/UKBB_phen_29983/olink_data_oct_2023.txt
   The QCed data: /proj/yunligrp/users/quansun/UKB_prot/ukbb_olink_data_oct_2023_ins_index_0_std_imp_invn.txt.gz
   Note: be sure to include "batch" as one covariate.
   /proj/yunligrp/users/djw/UKB_multiomics/rep_NM/proteomics_full.tab (***)

4. idsplit with different random states
   See ID split for 5 folds in folder: /proj/yunligrp/users/djw/UKB_multiomics/rep_NM/surv_res_phase2/idsplit_*.tab (***)
   If you are only using individuals with full records in both metabolomics and proteomics, please use "idsplit_overlap", sample size ~22k for most traits (decrease to ~ half in sex specific traits: breast cancer and prostate cancer);
   Else if you tend to use only metabolomics data, please use "idsplit_full", sample size ~277k with individuals have full record of metabolomics record.