Developer

This GWAS analysis pipeline is released by the author of the DOI: 10.1093/eurheartj/ehae206 ^[1].

Data

It was tested on the CLHLS dataset (13226 samples, 27233 genetic variants).

Workflow

It follows the guidelines of Marees's Study^[2].

Reference

[1]Yuebin Lv, et al. Body mass index, waist circumference, and mortality in subjects older than 80 years: a Mendelian randomization study, European Heart Journal, Volume 45, Issue 24, 21 June 2024
[2]Marees AT, et al.A tutorial on conducting genome-wide association studies: Quality control and statistical analysis,International Journal of Methods in Psychiatric Researc, e1608 (2018).

Background

This workflow was used in the Yuebin Lv's article^[1].

Quality Control

The samples and genetic variants were quality controled using the PLINK software. The genotype imputation was processed by IMPUTE (version 2.3.2)

Results

Reference

[1]Yuebin Lv, et al. Body mass index, waist circumference, and mortality in subjects older than 80 years: a Mendelian randomization study, European Heart Journal, Volume 45, Issue 24, 21 June 2024

Versions

V1.0 using the computational environment in Software repository: SRS568983209204002816, using script in Coding repository: CRS593944439333072896

1. Compress data

Compress the ped and map files into one rar file, and please don't include folder

2. Select the workflow

3. Fill in the name of the ped file

4. Upload the data and submit the task

5. View the analysis result