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Presentation . 2023
License: CC BY
Data sources: Datacite
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Other literature type . 2023
License: CC BY
Data sources: ZENODO
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Presentation . 2023
License: CC BY
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MR-AHC: A fast, efficient and robust method for two-sample summary data Mendelian Randomization based on Agglomerative Hierarchical Clustering

descriptionPublicationkeyboard_double_arrow_right Presentation , Other literature type 02 Mar 2023 English Publisher:Zenodo
Authors: Liang, Xiaoran;

doi: 10.5281/zenodo.7752180 , 10.5281/zenodo.7752179

MR-AHC: A fast, efficient and robust method for two-sample summary data Mendelian Randomization based on Agglomerative Hierarchical Clustering

Abstract

Slides presented by Dr Xiaoran Liang at the Early Career Researcher Lunchtime session on 2 March 2023. This series of sessions is organised by the Research Support Facility of the AI for Multiple Long-term Conditions programme.

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Keywords

MLTC, Multimorbidity, Causal Inference, GWAS, Mendelian Randomization

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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