README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# gtexr <a href="https://rmgpanw.github.io/gtexr/"><img src="man/figures/logo.png" align="right" height="138"/></a>

<!-- badges: start -->

[![pkgdown](https://github.com/rmgpanw/gtexr/actions/workflows/pkgdown.yaml/badge.svg)](https://github.com/rmgpanw/gtexr/actions/workflows/pkgdown.yaml) [![Codecov test coverage](https://codecov.io/gh/rmgpanw/gtexr/branch/main/graph/badge.svg)](https://app.codecov.io/gh/rmgpanw/gtexr?branch=main) [![R-CMD-check](https://github.com/rmgpanw/gtexr/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/rmgpanw/gtexr/actions/workflows/R-CMD-check.yaml) [![Deploy to shinyapps.io](https://github.com/rmgpanw/gtexr/actions/workflows/shinyapps-deploy.yaml/badge.svg)](https://github.com/rmgpanw/gtexr/actions/workflows/shinyapps-deploy.yaml) [![CRAN status](https://www.r-pkg.org/badges/version/gtexr)](https://CRAN.R-project.org/package=gtexr) [![CRAN downloads](https://cranlogs.r-pkg.org/badges/gtexr)](https://CRAN.R-project.org/package=gtexr)

<!-- badges: end -->

The goal of gtexr is to provide a convenient R interface to the [GTEx Portal API V2](https://gtexportal.org/api/v2/redoc#tag/GTEx-Portal-API-Info).

New to R? Try out the ⭐[shiny app](https://7hocgq-rmgpanw.shinyapps.io/gtexr/)⭐.

## Installation

You can install this package from CRAN:

``` r
install.packages("gtexr")
```

Or you can install the development version  of gtexr from [GitHub](https://github.com/rmgpanw/gtexr) with:

``` r
# install.packages("devtools")
devtools::install_github("rmgpanw/gtexr")
```

## Examples

Get general information about the GTEx service:

```{r}
library(gtexr)
get_service_info()
```

Retrieve eQTL genes for whole blood tissue:

```{r get-eqtl-genes}
get_eqtl_genes("Whole_Blood")
```

Retrieve significant eQTLs for one or more genes:

```{r get-significant-single-tissue-eqtls}
get_significant_single_tissue_eqtls(gencodeId = c("ENSG00000132693.12",
                                                  "ENSG00000203782.5"))
```