Merge pull request #622 from remlapmot/devel [skip ci]

remlapmot · web-flow · commit d04b847aef64 · 2025-04-20T10:54:43.000+01:00
Use a skip helper function and some minor amends to two vignettes
diff --git a/tests/testthat/helper-twosamplemr.R b/tests/testthat/helper-twosamplemr.R
@@ -0,0 +1,7 @@
+skip_if_opengwas_tests_disabled <- function() {
+  if (!identical(Sys.getenv("TWOSAMPLEMR_ENABLE_OPENGWAS_TESTS"), "TRUE")) {
+    skip("Tests requiring OpenGWAS.")
+  } else {
+    invisible()
+  }
+}
diff --git a/tests/testthat/test_add_metadata.r b/tests/testthat/test_add_metadata.r
@@ -1,6 +1,6 @@
 context("add metadata")
 
-skip_if(Sys.getenv('TWOSAMPLEMR_ENABLE_OPENGWAS_TESTS') != TRUE, "Tests requiring OpenGWAS")
+skip_if_opengwas_tests_disabled()
 skip_if_offline()
 skip_if_offline(host = "api.opengwas.io")
 skip_on_cran()
diff --git a/tests/testthat/test_create_test_data.r b/tests/testthat/test_create_test_data.r
@@ -1,5 +1,5 @@
 test_that("Create local data", {
-  skip_if(Sys.getenv('TWOSAMPLEMR_ENABLE_OPENGWAS_TESTS') != TRUE, "Tests requiring OpenGWAS")
+skip_if_opengwas_tests_disabled()
 skip("Skip local data creation unless you have good access to the API.")
 
 exp_dat <- extract_instruments("ieu-a-2")
diff --git a/tests/testthat/test_instruments.R b/tests/testthat/test_instruments.R
@@ -1,6 +1,6 @@
 context("Instruments")
 
-skip_if(Sys.getenv('TWOSAMPLEMR_ENABLE_OPENGWAS_TESTS') != TRUE, "Tests requiring OpenGWAS")
+skip_if_opengwas_tests_disabled()
 skip_if_offline()
 skip_if_offline(host = "api.opengwas.io")
 skip_on_cran()
diff --git a/tests/testthat/test_ld.R b/tests/testthat/test_ld.R
@@ -1,6 +1,6 @@
 context("ld")
 
-skip_if(Sys.getenv('TWOSAMPLEMR_ENABLE_OPENGWAS_TESTS') != TRUE, "Tests requiring OpenGWAS")
+skip_if_opengwas_tests_disabled()
 skip_if_offline()
 skip_if_offline(host = "api.opengwas.io")
 skip_on_cran()
diff --git a/tests/testthat/test_ldsc.R b/tests/testthat/test_ldsc.R
@@ -1,7 +1,7 @@
 context("LDSC")
 
 test_that("get afl2", {
-  skip_if(Sys.getenv('TWOSAMPLEMR_ENABLE_OPENGWAS_TESTS') != TRUE, "Tests requiring OpenGWAS")
+  skip_if_opengwas_tests_disabled()
 	skip("Very slow")
 	hm3info <- ieugwasr::afl2_list("hapmap3")
 	if(inherits(hm3info, "response")) skip("Server issues")
diff --git a/tests/testthat/test_mvmr.R b/tests/testthat/test_mvmr.R
@@ -1,6 +1,6 @@
 context("mvmr")
 
-skip_if(Sys.getenv('TWOSAMPLEMR_ENABLE_OPENGWAS_TESTS') != TRUE, "Tests requiring OpenGWAS")
+skip_if_opengwas_tests_disabled()
 skip_on_cran()
 skip_if_offline()
 skip_if_offline(host = "api.opengwas.io")
diff --git a/tests/testthat/test_mvmr_local.R b/tests/testthat/test_mvmr_local.R
@@ -10,7 +10,7 @@ context("mvmr local")
 load(system.file("extdata", "test_add_mvmr_local.RData", package="TwoSampleMR"))
 
 test_that("mv exposure local", {
-  skip_if(Sys.getenv('TWOSAMPLEMR_ENABLE_OPENGWAS_TESTS') != TRUE, "Tests requiring OpenGWAS")
+  skip_if_opengwas_tests_disabled()
   skip_if_offline()
   skip_if_offline(host = "api.opengwas.io")
 	skip_on_cran()
diff --git a/tests/testthat/test_otherformats.R b/tests/testthat/test_otherformats.R
@@ -13,7 +13,7 @@ test_that("MRInput", {
 })
 
 test_that("MRInput with cor", {
-  skip_if(Sys.getenv('TWOSAMPLEMR_ENABLE_OPENGWAS_TESTS') != TRUE, "Tests requiring OpenGWAS")
+  skip_if_opengwas_tests_disabled()
   skip_on_cran()
   skip_if_offline()
   skip_if_offline(host = "api.opengwas.io")
diff --git a/tests/testthat/test_outcomes.R b/tests/testthat/test_outcomes.R
@@ -1,6 +1,6 @@
 context("outcome")
 
-skip_if(Sys.getenv('TWOSAMPLEMR_ENABLE_OPENGWAS_TESTS') != TRUE, "Tests requiring OpenGWAS")
+skip_if_opengwas_tests_disabled()
 skip_if_offline()
 skip_if_offline(host = "api.opengwas.io")
 skip_on_cran()
diff --git a/tests/testthat/test_rsq.r b/tests/testthat/test_rsq.r
@@ -10,7 +10,7 @@ test_that("exposure data 1", {
 })
 
 test_that("exposure data 2", {
-  skip_if(Sys.getenv('TWOSAMPLEMR_ENABLE_OPENGWAS_TESTS') != TRUE, "Tests requiring OpenGWAS")
+  skip_if_opengwas_tests_disabled()
   skip_if_offline()
   skip_if_offline(host = "api.opengwas.io")
   skip_on_cran()
@@ -24,7 +24,7 @@ test_that("exposure data 2", {
 exposure <- exp_dat[1:5,]
 
 test_that("outcome data 1", {
-  skip_if(Sys.getenv('TWOSAMPLEMR_ENABLE_OPENGWAS_TESTS') != TRUE, "Tests requiring OpenGWAS")
+  skip_if_opengwas_tests_disabled()
   skip_if_offline()
   skip_if_offline(host = "api.opengwas.io")
   skip_on_cran()
@@ -38,7 +38,7 @@ test_that("outcome data 1", {
 })
 
 test_that("outcome data 2", {
-  skip_if(Sys.getenv('TWOSAMPLEMR_ENABLE_OPENGWAS_TESTS') != TRUE, "Tests requiring OpenGWAS")
+  skip_if_opengwas_tests_disabled()
   skip_if_offline()
   skip_if_offline(host = "api.opengwas.io")
   skip_on_cran()
@@ -52,7 +52,7 @@ test_that("outcome data 2", {
 })
 
 test_that("dat 2", {
-  skip_if(Sys.getenv('TWOSAMPLEMR_ENABLE_OPENGWAS_TESTS') != TRUE, "Tests requiring OpenGWAS")
+  skip_if_opengwas_tests_disabled()
   skip_if_offline()
   skip_if_offline(host = "api.opengwas.io")
   skip_on_cran()
@@ -64,7 +64,7 @@ test_that("dat 2", {
 })
 
 test_that("dat ukb-d", {
-  skip_if(Sys.getenv('TWOSAMPLEMR_ENABLE_OPENGWAS_TESTS') != TRUE, "Tests requiring OpenGWAS")
+  skip_if_opengwas_tests_disabled()
   skip_if_offline()
   skip_if_offline(host = "api.opengwas.io")
   skip_on_cran()
@@ -82,7 +82,7 @@ test_that("effective n", {
 })
 
 test_that("get_population_allele_frequency", {
-  skip_if(Sys.getenv('TWOSAMPLEMR_ENABLE_OPENGWAS_TESTS') != TRUE, "Tests requiring OpenGWAS")
+  skip_if_opengwas_tests_disabled()
   skip_if_offline()
   skip_if_offline(host = "api.opengwas.io")
   skip_on_cran()
@@ -100,7 +100,7 @@ test_that("get_population_allele_frequency", {
 })
 
 test_that("bbj-a-1", {
-  skip_if(Sys.getenv('TWOSAMPLEMR_ENABLE_OPENGWAS_TESTS') != TRUE, "Tests requiring OpenGWAS")
+  skip_if_opengwas_tests_disabled()
   skip_on_cran()
   skip_if_offline()
   skip_if_offline(host = "api.opengwas.io")
@@ -112,7 +112,7 @@ test_that("bbj-a-1", {
 })
 
 test_that("bsen vs pn", {
-  skip_if(Sys.getenv('TWOSAMPLEMR_ENABLE_OPENGWAS_TESTS') != TRUE, "Tests requiring OpenGWAS")
+  skip_if_opengwas_tests_disabled()
   skip_if_offline()
   skip_if_offline(host = "api.opengwas.io")
   skip_on_cran()
diff --git a/vignettes/gwas2020.Rmd b/vignettes/gwas2020.Rmd
@@ -7,7 +7,7 @@ vignette: >
   %\VignetteEncoding{UTF-8}
 ---
 
-This document details changes and new features specifically relating to the TwoSampleMR R package and the GWAS database behind it.
+This document details changes and new features specifically relating to the TwoSampleMR R package and the IEU OpenGWAS database behind it.
 
 ## What has changed
 
@@ -19,7 +19,7 @@ There is backward compatibility built into the R packages that access the data,
 
 ### Authentication
 
-Previously you would automatically be asked to authenticate any query to the database, through google. Now, we are making authentication voluntary - something that you do at the start of a session only if you need access to specific private datasets on the database. For the vast majority of use cases this is not required.
+Previously you would automatically be asked to authenticate any query to the database, through Google. Now, we are making authentication voluntary - something that you do at the start of a session only if you need access to specific private datasets on the database. For the vast majority of use cases this is not required.
 
 Another change is that the R package that managed the authentication has updated, and the file tokens generated are slightly different. For full information on how to deal with this, see here: https://mrcieu.github.io/ieugwasr/articles/guide.html#authentication
 
@@ -97,35 +97,17 @@ Either the data in the database, or the GWAS VCF files, can be queried and the r
 
 ## Key links
 
-- The IEU GWAS database: https://gwas.mrcieu.ac.uk
-- API to the IEU GWAS database: https://api.opengwas.io/api/
+- The IEU OpenGWAS database: https://gwas.mrcieu.ac.uk
+- API to the IEU OpenGWAS database: https://api.opengwas.io/api/
 - ieugwasr package, for R access to the API: https://mrcieu.github.io/ieugwasr/
-- ieugwaspy package, for python access to the API: https://github.com/MRCIEU/ieugwaspy/ (Under construction)
+- ieugwaspy package, for python access to the API: https://github.com/MRCIEU/ieugwaspy/
 - gwasvcf package, R interface to GWAS VCF files: https://mrcieu.github.io/gwasvcf/
-- pygwasvcf package, python interface to GWAS VCF files: https://github.com/mrcieu/pygwasvcf (Under construction)
-- gwasglue package, linking GWAS data to various analytical methods: https://mrcieu.github.io/gwasglue/ (Functional, under construction)
+- pygwasvcf package, python interface to GWAS VCF files: https://github.com/mrcieu/pygwasvcf
+- gwasglue package, linking GWAS data to various analytical methods: https://mrcieu.github.io/gwasglue/
 - gwas2vcf online tool, allowing users to create GWAS VCF files from summary data: https://github.com/MRCIEU/gwas2vcf
 
 ## How to request new data
 
 We have setup a github issues page here: https://github.com/MRCIEU/opengwas-requests/issues
 
 Please visit here to make a log of new data requests, or to contribute new data.
-
-## Backwards compatibility
-
-To install the new version of TwoSampleMR, perform as normal:
-
-```r
-install.packages("remotes")
-remotes::install_github("MRCIEU/TwoSampleMR")
-```
-
-To update the package just run the `remotes::install_github("MRCIEU/TwoSampleMR")` command again.
-
-We recommend using this new version going forwards but for a limited time we are enabling backwards compatibility, in case you are in the middle of analysis or need to reproduce old analysis. In order to use the legacy version of the package and the database, install using:
-
-```r
-install.packages("remotes")
-remotes::install_github("MRCIEU/TwoSampleMR@0.4.26")
-```
diff --git a/vignettes/introduction.Rmd b/vignettes/introduction.Rmd
@@ -22,26 +22,60 @@ knitr::opts_chunk$set(
 
 ## Background
 
-Two sample Mendelian randomisation (2SMR) is a method to estimate the causal effect of an exposure on an outcome using only summary statistics from genome wide association studies (GWAS). Though conceptually straightforward, there are a number of steps that are required to perform the analysis properly, and they can be cumbersome. The TwoSampleMR package aims to make this easy by combining three important components
+Two sample Mendelian randomisation is a method to estimate the causal effect of an exposure on an outcome using only summary statistics from genome wide association studies (GWAS). Though conceptually straightforward, there are a number of steps that are required to perform the analysis properly, and they can be cumbersome. The TwoSampleMR package aims to make this easy by combining three important components
 
 - data management and harmonisation
 - the statistical routines to estimate the causal effects
 - connection to a large repository of the actual GWAS summary statistics needed to perform the analyses.
 
 The general principles [@DaveySmith2003; @DaveySmithHemani2014], and statistical methods [@Pierce2013; @Bowden2015] can be found elsewhere, here we will just outline how to use the R package.
 
-This package uses the [ieugwasr](https://github.com/mrcieu/ieugwasr) package to connect to the database of thousands of complete GWAS summary data.
+This package uses the [ieugwasr](https://github.com/mrcieu/ieugwasr) package to connect to the IEU OpenGWAS database of thousands of complete GWAS summary data.
 
 ## Installation
 
-To install directly from the GitHub repository do the following:
+If you are using macOS or Windows you can install a binary version of TwoSampleMR from our <https://mrcieu.r-universe.dev> with the following code.
 
 ```{r eval=FALSE}
+install.packages("TwoSampleMR", repos = c("https://mrcieu.r-universe.dev", "https://cloud.r-project.org"))
+```
+
+If you are using the latest long term support version of Ubuntu Linux (currently 24.04 Noble Numbat) you can install a binary version of TwoSampleMR with the following code.
+
+```{r eval=FALSE}
+options(HTTPUserAgent = sprintf(
+  "R/%s R (%s)",
+  getRversion(),
+  paste(getRversion(),
+        R.version["platform"],
+        R.version["arch"],
+        R.version["os"])
+))
+
+install.packages(
+  'TwoSampleMR',
+  repos = c(
+    'https://mrcieu.r-universe.dev/bin/linux/noble/4.5/',
+    'https://p3m.dev/cran/__linux__/noble/latest',
+    'https://cloud.r-project.org'
+  )
+)
+```
+
+To install TwoSampleMR from source from our GitHub repository run the following code.
+
+```{r eval=FALSE}
+# install.packages("remotes") # Run if remotes package not installed
 library(remotes)
 install_github("MRCIEU/TwoSampleMR")
 ```
 
-If you don't have the `remotes` package install it from CRAN using `install.packages("remotes")`.
+TwoSampleMR can be installed in [WebR](https://docs.r-wasm.org/webr/latest/) using the following code.
+
+```{r eval=FALSE}
+install.packages('TwoSampleMR',
+  repos = c('https://mrcieu.r-universe.dev', 'https://repo.r-wasm.org'))
+```
 
 ## Overview
 
@@ -70,7 +104,7 @@ ao <- available_outcomes()
 exposure_dat <- extract_instruments("ieu-a-2")
 
 # Get effects of instruments on outcome
-outcome_dat <- extract_outcome_data(snps=exposure_dat$SNP, outcomes = "ieu-a-7")
+outcome_dat <- extract_outcome_data(snps = exposure_dat$SNP, outcomes = "ieu-a-7")
 
 # Harmonise the exposure and outcome data
 dat <- harmonise_data(exposure_dat, outcome_dat)
