Last updated: 2020-08-20
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Knit directory: SlopeHunter/
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File | Version | Author | Date | Message |
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Rmd | 0201448 | Osama | 2020-07-24 | Update Readme |
html | 0201448 | Osama | 2020-07-24 | Update Readme |
Rmd | ac4f0d8 | Osama | 2020-07-24 | R package built |
Rmd | 8499789 | Osama | 2020-07-23 | Test |
html | 8499789 | Osama | 2020-07-23 | Test |
Rmd | bb0225b | Osama | 2020-07-23 | test ws |
html | bb0225b | Osama | 2020-07-23 | test ws |
Rmd | daef612 | Osama | 2020-07-23 | test ws |
Rmd | 17c2707 | Osama | 2020-07-23 | Test ws |
html | 17c2707 | Osama | 2020-07-23 | Test ws |
Rmd | 85d883b | Osama | 2020-07-23 | Test ws |
html | 85d883b | Osama | 2020-07-23 | Test ws |
Rmd | 91edbca | Osama | 2020-07-23 | Test website |
html | 91edbca | Osama | 2020-07-23 | Test website |
html | 853776a | Osama | 2020-07-23 | Initial step |
Rmd | 95f08ec | Osmahmoud | 2020-07-23 | Start workflowr project. |
Some useful links are as follows:
Website of the corresponding author
This website layout was inspired by the layout of the CAUSE website.
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.