add global var, minor fixes

can add WORDLIST later, as needed. @AbhirupaGhosh @epbrenner @eboyer221

Author: jananiravi

NAMESPACE

@@ -1,6 +1,7 @@
 # Generated by roxygen2: do not edit by hand
 
 export(launchAMRDashboard)
+import(shiny)
 importFrom(ComplexHeatmap,Heatmap)
 importFrom(ComplexHeatmap,draw)
 importFrom(DBI,dbConnect)
@@ -14,11 +15,14 @@ importFrom(dplyr,all_of)
 importFrom(dplyr,arrange)
 importFrom(dplyr,bind_rows)
 importFrom(dplyr,c_across)
+importFrom(dplyr,case_when)
 importFrom(dplyr,collect)
+importFrom(dplyr,count)
 importFrom(dplyr,desc)
 importFrom(dplyr,distinct)
 importFrom(dplyr,filter)
 importFrom(dplyr,group_by)
+importFrom(dplyr,join_by)
 importFrom(dplyr,left_join)
 importFrom(dplyr,mutate)
 importFrom(dplyr,n)
@@ -27,8 +31,10 @@ importFrom(dplyr,rowwise)
 importFrom(dplyr,select)
 importFrom(dplyr,slice_head)
 importFrom(dplyr,slice_max)
+importFrom(dplyr,summarise)
 importFrom(dplyr,summarize)
 importFrom(dplyr,ungroup)
+importFrom(dplyr,where)
 importFrom(duckdb,duckdb)
 importFrom(ggplot2,aes)
 importFrom(ggplot2,coord_cartesian)

R/globals.R

@@ -0,0 +1,49 @@
+# Global variables for NSE (Non-Standard Evaluation)
+# These are column names used in dplyr/data.table operations
+# Declaring them here silences R CMD check notes about "no visible binding"
+
+utils::globalVariables(c(
+
+  # Column names used across the package
+  "ARG_name",
+  "COG_name",
+  "Gene",
+
+  "Importance",
+  "Variable",
+  "accession",
+  "bal_acc",
+  "configurations",
+  "count",
+  "data_type",
+  "drug.antibiotic_name",
+  "drug_class",
+  "drug_classes",
+  "drug_count",
+  "drug_level",
+  "drug_or_class_name",
+  "drug_or_drug_class",
+  "feature_type",
+  "genome.collection_year",
+  "genome.host_common_name",
+  "genome.isolation_country",
+  "genome.isolation_source",
+  "genome.isolation_source_",
+  "genome_drug.antibiotic",
+  "genome_drug.resistant_phenotype",
+  "group",
+  "max_imp",
+  "nmcc",
+  "predicted_drug",
+  "proteinID",
+  "source_file",
+  "species",
+  "species_count",
+  "tested_country",
+  "tested_year",
+  "trained_country",
+  "trained_year",
+
+ # data.table operator
+ ":="
+))

R/utils.R

@@ -1,7 +1,8 @@
 #' @importFrom shinydashboard box tabBox
 #' @importFrom dplyr filter mutate select group_by summarize ungroup arrange
 #' @importFrom dplyr pull distinct left_join bind_rows slice_max slice_head
-#' @importFrom dplyr collect desc n c_across all_of rowwise
+#' @importFrom dplyr collect desc n c_across all_of rowwise case_when join_by
+#' @importFrom dplyr count summarise where
 #' @importFrom ggplot2 ggplot aes geom_col geom_line geom_point geom_boxplot
 #' @importFrom ggplot2 theme_bw theme_minimal theme element_text labs
 #' @importFrom ggplot2 scale_fill_brewer scale_color_brewer coord_cartesian

README.Rmd

@@ -17,13 +17,11 @@ knitr::opts_chunk$set(
 
 <!-- badges: start -->
 [![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
-[![CRAN status](https://www.r-pkg.org/badges/version/NewShinyPackage)](https://CRAN.R-project.org/package=NewShinyPackage)
-[![R-CMD-check](https://github.com/JRaviLab/NewShinyPackage/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/JRaviLab/NewShinyPackage/actions/workflows/R-CMD-check.yaml)
 <!-- badges: end -->
 
 **amRshiny** is an interactive Shiny dashboard for exploring antimicrobial resistance (AMR) data and machine learning model results.
 
-Part of the **AMR package suite**, [JRaviLab/amR](https://github.com/jravilab/amR):
+This is the final package in the **AMR package suite**, [JRaviLab/amR](https://github.com/jravilab/amR):
 
 - **amRdata**: Data (and metadata) preparation from BV-BRC
 - **amRml**: ML modeling and analysis
@@ -59,24 +57,6 @@ if (!requireNamespace("devtools", quietly = TRUE))
 devtools::install_github("JRaviLab/amRshiny")
 ```
 
-### Future (Bioconductor release)
-
-Once submitted to Bioconductor, installation will be:
-
-```r
-if (!requireNamespace("BiocManager", quietly = TRUE))
-    install.packages("BiocManager")
-
-BiocManager::install("amRshiny")
-```
-
-### Optional dependencies
-
-```r
-# For enhanced data processing
-BiocManager::install("arrow")
-```
-
 ## Quick start
 
 ```r
@@ -118,12 +98,12 @@ The dashboard includes several tabs:
 ### Example: Exploring model performance
 
 ```r
-launch_dashboard()
+launchAMRDashboard()
 
 # In the dashboard:
 # 1. Navigate to "Model Performance" tab
-# 2. Select species: "Campylobacter jejuni"
-# 3. Select drug: "ciprofloxacin"
+# 2. Select species: "Shigella flexneri"
+# 3. Select drug: "ampicillin"
 # 4. Select molecular scale: "genes"
 # 5. View performance metrics and confusion matrix
 ```

README.md

@@ -7,15 +7,12 @@
 
 [![Lifecycle:
 experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
-[![CRAN
-status](https://www.r-pkg.org/badges/version/NewShinyPackage)](https://CRAN.R-project.org/package=NewShinyPackage)
-[![R-CMD-check](https://github.com/JRaviLab/NewShinyPackage/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/JRaviLab/NewShinyPackage/actions/workflows/R-CMD-check.yaml)
 <!-- badges: end -->
 
 **amRshiny** is an interactive Shiny dashboard for exploring
 antimicrobial resistance (AMR) data and machine learning model results.
 
-Part of the **AMR package suite**,
+This is the final package in the **AMR package suite**,
 [JRaviLab/amR](https://github.com/jravilab/amR):
 
 - **amRdata**: Data (and metadata) preparation from BV-BRC
@@ -57,24 +54,6 @@ if (!requireNamespace("devtools", quietly = TRUE))
 devtools::install_github("JRaviLab/amRshiny")
 ```
 
-### Future (Bioconductor release)
-
-Once submitted to Bioconductor, installation will be:
-
-``` r
-if (!requireNamespace("BiocManager", quietly = TRUE))
-    install.packages("BiocManager")
-
-BiocManager::install("amRshiny")
-```
-
-### Optional dependencies
-
-``` r
-# For enhanced data processing
-BiocManager::install("arrow")
-```
-
 ## Quick start
 
 ``` r
@@ -116,12 +95,12 @@ The dashboard includes several tabs:
 ### Example: Exploring model performance
 
 ``` r
-launch_dashboard()
+launchAMRDashboard()
 
 # In the dashboard:
 # 1. Navigate to "Model Performance" tab
-# 2. Select species: "Campylobacter jejuni"
-# 3. Select drug: "ciprofloxacin"
+# 2. Select species: "Shigella flexneri"
+# 3. Select drug: "ampicillin"
 # 4. Select molecular scale: "genes"
 # 5. View performance metrics and confusion matrix
 ```
@@ -205,8 +184,8 @@ Report bugs and request features at:
 
 ## Related projects
 
-- [amRdata](https://github.com/JRaviLab/amRdata): Data preparation
-  pipeline
+- [amRdata](https://github.com/JRaviLab/amRdata): Data preparation for
+  AMR prediction
 - [amRml](https://github.com/JRaviLab/amRml): ML modeling framework
 - [BV-BRC](https://www.bv-brc.org/): Bacterial and Viral Bioinformatics
   Resource Center