Protocols

Below we provide step-by-step scripts from two papers. They are designed to be run as bash scripts on a UNIX operating system, but should also work in Terminal on a MAC (but are not suitable for Windows). A backslash (\) at the end of a line indicates a command continues onto the next line. Where mentioned, commands can be run in parallel; access to a cluster is highly recommended when performing imputation and when calculating SNP weightings for data that includes rare variants.

Please note that when calculating kinships and tagging files, these scripts use the LDAK Model. We now recommend using either the LDAK-Thin or BLD-LDAK Model. Heritability Models provides more details, while Calculate Kinships and Calculate Taggings explain how to implement the new heritability models.
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SumHer better estimates the SNP heritability of complex traits from summary statistics, Nature Genetics, 2019.

The scripts below provide step-by-step details for each of the analyses we performed. For a fuller explanation, see the relevant sections in SumHer.

Obtain reference panel, format summary statistics, estimate SNP heritability and confounding
Estimate enrichments and genetic correlations
Construct polygenic risk scores and simulate phenotypes
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Reevaluation of SNP heritability in complex human traits, Nature Genetics, 2017.

The first three files provide step-by-step instructions for estimating SNP heritability using REML, starting with raw genotype data. The imputation guide requires a (phased) reference panel; we used 1000 Genomes Phase 3 (October 2014), which we downloaded from the IMPUTE2 website. The fourth file provides tips for advanced analyses, including computing enrichment of a SNP set and estimating heritability when there are rare variants.

Imputing Cohorts
Merging Cohorts
Estimating SNP Heritability

Advanced Analysis

Weblinks:
PLINK | SHAPEIT | IMPUTE2 | Genome Browser
LiftOver which uses the files RsMergeArch.bcp.gz and SNPHistory.bcp.gz
Details of our imputation regions