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Obtaining summary data from genomes wide association studies

PH Philip C Haycock

Last updated date: Apr 1, 2020 Views: 1249 Forks: 0

original An abbreviated version of this protocol was published in eLife in May, 2018
The MR-Base platform supports systematic causal inference across the human phenome
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Thank you for agreeing to share summary data with MR-Base.  




Please could you provide the following summary data for each SNP:

1. Regression coefficient for each SNP 

2. Standard error for the regression coefficient

3. Effect allele (i.e. the coded allele)

4. Non-effect allele

5. Effect allele frequency


The following metrics of genotype quality would also be helpful if available:

6. P values for Hardy–Weinberg equilibrium

7. P values / Cochran's Q test for between study heterogeneity

8. Metrics of SNP imputation quality, such as info / r2 scores (for imputed SNPs)




We are also seeking the following information (please provide as much as possible):

9. A PubMed identifier (PMID) for a paper we can use as a reference for the methods used to produce the summary data

10. Confirmation that the summary data have been through the same post-GWAS filtering / quality control procedures described in the published paper 

11. Sample size or number of cases and controls in the GWAS analysis

12. Genome build and reference strand

13. Geographic origins for study participants (e.g. East Asian, European, etc)




 





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How to cite：
Readers should cite both the Bio-protocol preprint and the original research article where this protocol was used:
  1. Haycock, P(2020). Obtaining summary data from genomes wide association studies. Bio-protocol Preprint. bio-protocol.org/prep260.
  2. Hemani, G., Zheng, J., Elsworth, B., Wade, K. H., Haberland, V., Baird, D., Laurin, C., Burgess, S., Bowden, J., Langdon, R., Tan, V. Y., Yarmolinsky, J., Shihab, H. A., Timpson, N. J., Evans, D. M., Relton, C., Martin, R. M., Davey Smith, G., Gaunt, T. R. and Haycock, P. C.(2018). The MR-Base platform supports systematic causal inference across the human phenome. eLife. DOI: 10.7554/eLife.34408

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