(Q28660901)

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Meta-analysis of genome-wide association studies: no efficiency gain in using individual participant data

scientific article (publication date: 2010)

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Meta-analysis of genome-wide association studies: no efficiency gain in using individual participant data (English)

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main subject

genome-wide association study

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meta-analysis

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author name string

D Y Lin

series ordinal

1

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D Zeng

series ordinal

2

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language of work or name

English

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publication date

January 2010

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published in

Genetic Epidemiology

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volume

34

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issue

1

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page(s)

60-6

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cites work

A framework for interpreting genome-wide association studies of psychiatric disorders

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17 March 2017

Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes

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17 March 2017

Principal components analysis corrects for stratification in genome-wide association studies

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17 March 2017

Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes

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7 April 2017

A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants

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7 April 2017

Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels

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7 April 2017

On the relative efficiency of using summary statistics versus individual-level data in meta-analysis

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3 June 2018

Methods for meta-analysis in genetic association studies: a review of their potential and pitfalls

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3 June 2018

Comparison of meta-analysis versus analysis of variance of individual patient data

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(Q28660901)

Meta-analysis of genome-wide association studies: no efficiency gain in using individual participant data

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