Removing o2groups dependency in the vignette (causing error) by addin…

…g sim_tree.rda instead.

.github/workflows/R-CMD-check.yaml

@@ -40,10 +40,6 @@ jobs:
           http-user-agent: ${{ matrix.config.http-user-agent }}
           use-public-rspm: true
 
-      - name: Install o2groups from GitHub
-        run: |
-          R -e "remotes::install_github('CyGei/o2groups')"
-
       - uses: r-lib/actions/setup-r-dependencies@v2
         with:
           extra-packages: any::rcmdcheck

.github/workflows/test-coverage.yaml

@@ -0,0 +1,61 @@
+# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
+# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
+on:
+  push:
+    branches: [main, master]
+  pull_request:
+
+name: test-coverage.yaml
+
+permissions: read-all
+
+jobs:
+  test-coverage:
+    runs-on: ubuntu-latest
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: r-lib/actions/setup-r@v2
+        with:
+          use-public-rspm: true
+
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::covr, any::xml2
+          needs: coverage
+
+      - name: Test coverage
+        run: |
+          cov <- covr::package_coverage(
+            quiet = FALSE,
+            clean = FALSE,
+            install_path = file.path(normalizePath(Sys.getenv("RUNNER_TEMP"), winslash = "/"), "package")
+          )
+          covr::to_cobertura(cov)
+        shell: Rscript {0}
+
+      - uses: codecov/codecov-action@v4
+        with:
+          # Fail if error if not on PR, or if on PR and token is given
+          fail_ci_if_error: ${{ github.event_name != 'pull_request' || secrets.CODECOV_TOKEN }}
+          file: ./cobertura.xml
+          plugin: noop
+          disable_search: true
+          token: ${{ secrets.CODECOV_TOKEN }}
+
+      - name: Show testthat output
+        if: always()
+        run: |
+          ## --------------------------------------------------------------------
+          find '${{ runner.temp }}/package' -name 'testthat.Rout*' -exec cat '{}' \; || true
+        shell: bash
+
+      - name: Upload test results
+        if: failure()
+        uses: actions/upload-artifact@v4
+        with:
+          name: coverage-test-failures
+          path: ${{ runner.temp }}/package

DESCRIPTION

@@ -17,14 +17,11 @@ Suggests:
     knitr,
     rmarkdown,
     testthat (>= 3.0.0),
-    remotes,
-    dplyr, 
+    pacman,
     epicontacts, 
     visNetwork
-Remotes:
-CyGei/o2groups
 Config/testthat/edition: 3
 Depends: 
-    R (>= 2.10)
+    R (>= 3.5)
 LazyData: true
 VignetteBuilder: knitr

R/simulated_tree.R → R/sim_tree.R

@@ -1,12 +1,26 @@
-#'Simulated transmission tree
-#' A simulated transmission tree generated from the `o2groups` package.
+#' Simulated transmission tree
 #'
-#' This dataset represents a simulated infection transmission tree, capturing the spread of an infectious disease within groups.
+#' This dataset represents a simulated transmission tree.
 #' This simulation was generated using the R package `o2groups` (see \url{https://github.com/CyGei/o2groups} for more information).
-#' Group `A` is assortative with a delta coefficient of 0.75 and group `B` is neutral with a delta coefficient of 0.
-#' Both group sizes were set at 100 individuals.
-#'
-#' @format A data frame with 151 rows and 6 columns:
+#' Group `HCW` is assortative with a gamma coefficient of 2 and group `patient` is disassortative with a gamma coefficient of 1/1.25.
+#' Suceptible group sizes were 100 and 350, respectively.
+#' Code to reproduce the data below:
+#' ```
+#' pacman::p_load_gh("CyGei/o2groups")
+#' set.seed(123)
+#' sim_tree <- o2groups::simulate_groups(
+#'   duration = 100,
+#'   group_n = 2,
+#'   size = c(100, 350), # susceptible group sizes
+#'   name = c("HCW", "patient"),
+#'   gamma = c(2, 0.8), # assortativity coefficients
+#'   intro_n = c(1, 3),
+#'   r0 = c(2, 2),
+#'   generation_time = c(0, 0.1, 0.2, 0.4, 0.2, 0.1, 0),
+#'   incubation_period = sample(1:14, 1000, replace = TRUE)
+#' )
+#'```
+#' @format A data frame with 373 rows and 6 columns:
 #' \describe{
 #'   \item{group}{Character. The group to which the individual belongs.}
 #'   \item{id}{Character. Unique identifier for each individual in the study.}
@@ -16,4 +30,4 @@
 #'   \item{date_onset}{Numeric. The date of onset of symptoms. Represented as the number of days since the start of the study.}
 #' }
 #' @source This dataset is simulated (see R package `o2groups`) and does not correspond to real-world data.
-"simulated_tree"
+"sim_tree"

README.Rmd

@@ -27,7 +27,7 @@ knitr::opts_chunk$set(
 <!-- badges: start -->
 
 [![R-CMD-check](https://github.com/CyGei/linktree/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/CyGei/linktree/actions/workflows/R-CMD-check.yaml)
-
+[![Codecov test coverage](https://codecov.io/gh/CyGei/linktree/graph/badge.svg)](https://app.codecov.io/gh/CyGei/linktree)
 <!-- badges: end -->
 
 `linktree` is a novel framework that leverages transmission chain data to estimate ***group transmission assortativity***; this quantifies the extent to which individuals transmit within their own group compared to others. The methodology is described in our [paper](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0313037).
@@ -36,7 +36,7 @@ knitr::opts_chunk$set(
 
 ```{r}
 # install.packages("devtools")
-devtools::install_github("CyGei/linktree")
+# devtools::install_github("CyGei/linktree")
 library(linktree)
 ```
 

README.md

@@ -14,7 +14,8 @@ linktree
 <!-- badges: start -->
 
 [![R-CMD-check](https://github.com/CyGei/linktree/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/CyGei/linktree/actions/workflows/R-CMD-check.yaml)
-
+[![Codecov test
+coverage](https://codecov.io/gh/CyGei/linktree/graph/badge.svg)](https://app.codecov.io/gh/CyGei/linktree)
 <!-- badges: end -->
 
 `linktree` is a novel framework that leverages transmission chain data
@@ -27,7 +28,7 @@ others. The methodology is described in our
 
 ``` r
 # install.packages("devtools")
-devtools::install_github("CyGei/linktree")
+# devtools::install_github("CyGei/linktree")
 library(linktree)
 ```
 

vignettes/linktree_vignette.Rmd

@@ -28,9 +28,7 @@ The goal of `linktree` is to estimate the transmission assortativity coefficient
 ## Installation
 
 ```{r}
-library(remotes)
-remotes::install_github("CyGei/linktree")
-library(linktree)
+pacman::p_load_gh("CyGei/linktree")
 ```
 
 ## Understanding the transmission assortativity coefficient
@@ -83,39 +81,26 @@ points(1, 0, col = "red", pch = 16)  # Homogeneous
 
 ### Data
 
-We can simulate an outbreak with multiple groups using the [`o2groups`](https://github.com/CyGei/o2groups) package and then use `linktree` to estimate the assortativity coefficients from the transmission tree.
+We can simulate an outbreak with multiple groups using the [`o2groups`](https://github.com/CyGei/o2groups) package and then use `linktree` to estimate the assortativity coefficients from the transmission tree. Below is a pre-loaded simulated transmission tree, see `?sim_tree` for more details.
 
 ```{r}
-remotes::install_github("CyGei/o2groups")
-library(o2groups)
-true_gamma <- c(2, 0.8) # assortativity coefficients
-
-set.seed(123)
-sim <- simulate_groups(
-  duration = 100,
-  group_n = 2,
-  size = c(100, 400),
-  name = c("HCW", "patient"),
-  gamma = true_gamma,
-  intro_n = c(1, 3),
-  r0 = c(1.7, 2),
-  generation_time = c(0, 0.1, 0.2, 0.4, 0.2, 0.1, 0),
-  incubation_period = sample(1:14, 1000, replace = TRUE)
-)
-head(sim)
+#?sim_tree
+true_gammas <- c(HCW = 2, patient = 1/1.25)
+sizes <- c(HCW = 100, patient = 350)
+data(sim_tree)
+head(sim_tree)
 ```
 
 ### Visualise the transmission tree
 
-```{r, message=FALSE}
+```{r, message=FALSE, warning=FALSE}
 remotes::install_github('reconhub/epicontacts@timeline')
-library(dplyr)
 library(epicontacts)
 library(visNetwork)
 
 x <- epicontacts::make_epicontacts(
-  linelist = dplyr::select(sim, c(group, id, date_infection, date_onset)),
-  contacts = dplyr::select(sim, c(source, id, source_group, group)),
+  linelist = sim_tree[, c("group", "id", "date_infection", "date_onset")],
+  contacts = sim_tree[, c("source", "id", "source_group", "group")],
   id = "id",
   from = "source",
   to = "id",
@@ -140,20 +125,18 @@ plot(x,
 ```
 
 ### Estimate the transmission assortativity coefficient
-
-
 Our published [paper](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0313037) provides guidelines as to when and under which circumstances we can reliably infer group transmission assortativity. Notably, we should analyse transmission chains up to the group's epidemic peak to avoid the saturation effect, and we should have at least ~30 cases in the group.
 
 ```{r, fig.width=8, fig.height=6, message=FALSE}
 est_delta <- get_delta(
-  from = sim$source_group,
-  to = sim$group,
-  f = c("HCW" = 100, "patient" = 400),
+  from = sim_tree$source_group,
+  to = sim_tree$group,
+  f = sizes,
 )
-true_delta <- gamma2delta(true_gamma)
+true_deltas <- gamma2delta(true_gammas)
 
 plot(est_delta, main = "Estimated vs True assortativity coefficients")
-abline(h = true_delta, col = c("#d53e4f", "#3288bd"), lty = 2)
+abline(h = true_deltas, col = c("#d53e4f", "#3288bd"), lty = 2)
 legend("topright", legend = c("HCW (truth)", "patient (truth)"), fill = c("#d53e4f", "#3288bd"), bty = "n")
 ```