index.Rmd

---
title: "Introduction to Slope-Hunter (Under Construction!)"
subtitle: "An approach for collider bias correction in GWAS of subsequent traits"
author: "Osama Mahmoud"
date: "July 23, 2020"
site: workflowr::wflow_site
output:
  workflowr::wflow_html:
    bibliography: sh.bib
    toc: true
    toc_depth: 2
editor_options:
  chunk_output_type: console
---

# Welcome to Slope-Hunter website!

Here are some useful links:

 [Pre-print of the manuscript](https://www.biorxiv.org/content/10.1101/2020.01.31.928077v1)
 
 [R package source](https://github.com/Osmahmoud/Slope-Hunter)
 
 [Website of the corresponding author](http://osmahmoud.com/)
 
 This website layout was inspired by the layout of the [CAUSE website](https://jean997.github.io/cause/index.html).

# Introduction to Slope-Hunter

Studying genetic associations with prognosis (e.g. survival, disability, subsequent disease events) is
problematic due to selection bias - also termed index event bias or collider bias - whereby selection
on disease status can induce associations between causes of incidence with prognosis.

The ‘Slope-Hunter’ approach is proposed for adjusting genetic associations for this bias. The approach is unbiased even when there is genetic correlation between incidence and prognosis.

Our approach has two stages. First, cluster-based techniques are used to identify: variants affecting neither incidence nor prognosis (these should not suffer bias and only a random sub-sample of them are retained in the analysis); variants affecting prognosis only (excluded from the analysis). Second, we fit a cluster-based model to identify the class of variants only affecting incidence, and use this class to estimate the adjustment factor.