README.Rmd

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csl: https://raw.githubusercontent.com/citation-style-language/styles/6152ccea8b7d7a472910d36524d1bf3557a83bfc/dependent/nature-genetics.csl
bibliography: references.bib
---

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```{r, include = FALSE}
knitr::opts_chunk$set(
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  fig.path = "man/figures/README-",
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)
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# ldscr

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The goal of ldscr is to provide functionality to estimate genetic heritability and cross-trait genetic correlations from GWAS summary statistics using LD score regression within R. Details of LD score regression for estimation of heritabliity and genetic correlations have been previously published.[@Bulik-Sullivan2015; @Bulik-Sullivan2015a] This package adapts code and functionality originally implemented in [GenomicSEM](https://github.com/GenomicSEM/GenomicSEM).[@Grotzinger2019]

## Installation

You can install the development version of ldscr from [GitHub](https://github.com/) with:

``` r
# install.packages("devtools")
devtools::install_github("mglev1n/ldscr")
```

## Usage

`ldsc_h2()` can be used to estimate heritability. Sample GWAS data is provided in `sumstats_munged_example()`. Users can utilize built-in LD reference data, or provide their own.

```{r ldsc_h2_example, eval=FALSE}
library(ldscr)
df <- sumstats_munged_example(example = "BMI")
h2_res <- ldsc_h2(munged_sumstats = df, ancestry = "EUR")
```

`ldsc_rg()` can be used to estimate cross-trait genetic correlations between two or more traits.

```{r ldsc_rg_example, eval=FALSE}
rg_res <- ldsc_rg(
  munged_sumstats = list(
    "APOB" = sumstats_munged_example(example = "APOB"),
    "LDL" = sumstats_munged_example(example = "LDL")
  ),
  ancestry = "EUR"
)
```

## References