Add plot_granges

DESCRIPTION

@@ -2,64 +2,70 @@ Package: AlphaMissenseR
 Title: Accessing AlphaMissense Data Resources in R
 Version: 1.1.5
 Authors@R:
-    c(person(
+        c(person(
         "Martin", "Morgan", role = c("aut", "cre"),
         email = "mtmorgan.xyz@gmail.com",
         comment = c(ORCID = "0000-0002-5874-8148")
-    ), person(
+        ), person(
         "Tram", "Nguyen",
         role = "aut"
-    ), person(
+        ), person(
+        "Tyrone", "Lee",
+        role = "ctb"
+        ), person(
+        "Nitesh", "Turaga",
+        role = "ctb"
+        ), person(
         "Chan Zuckerberg Initiative DAF CZF2019-002443",
         role = "fnd"
-    ), person(
+        ), person(
         "NIH NCI ITCR U24CA180996",
         role = "fnd"
-    ), person(
+        ), person(
         "NIH NCI IOTN U24CA232979",
         role = "fnd"
-    ), person(
+        ), person(
         "NIH NCI ARTNet U24CA274159",
         role = "fnd"
-    ))
+        ))
 Description:
-    The AlphaMissense publication
-    <https://www.science.org/doi/epdf/10.1126/science.adg7492>
-    outlines how a variant of AlphaFold / DeepMind was used to predict
-    missense variant pathogenicity. Supporting data on Zenodo
-    <https://zenodo.org/record/10813168> include, for instance, 71M
-    variants across hg19 and hg38 genome builds. The 'AlphaMissenseR'
-    package allows ready access to the data, downloading individual
-    files to DuckDB databases for exploration and integration into *R*
-    and *Bioconductor* workflows.
+        The AlphaMissense publication
+        <https://www.science.org/doi/epdf/10.1126/science.adg7492>
+        outlines how a variant of AlphaFold / DeepMind was used to predict
+        missense variant pathogenicity. Supporting data on Zenodo
+        <https://zenodo.org/record/10813168> include, for instance, 71M
+        variants across hg19 and hg38 genome builds. The 'AlphaMissenseR'
+        package allows ready access to the data, downloading individual
+        files to DuckDB databases for exploration and integration into *R*
+        and *Bioconductor* workflows.
 License: Artistic-2.0
 URL: https://mtmorgan.github.io/AlphaMissenseR/
 BugReports: https://github.com/mtmorgan/AlphaMissenseR/issues
 Depends:
-    R (>= 4.3.0),
-    dplyr
+        R (>= 4.3.0),
+        dplyr
 Imports:
-    rjsoncons (>= 1.0.1), DBI, duckdb (>= 0.9.1), rlang,
-    curl, BiocFileCache, spdl, memoise, BiocBaseUtils,
-    utils, stats, methods, whisker, ggplot2
+        rjsoncons (>= 1.0.1), DBI, duckdb (>= 0.9.1), rlang,
+        curl, BiocFileCache, spdl, memoise, BiocBaseUtils,
+        utils, stats, methods, whisker, ggplot2
 Suggests:
-    BiocManager,
-    BiocGenerics,
-    GenomicRanges,
-    GenomeInfoDb,
-    AnnotationHub,
-    ensembldb,
-    httr,
-    tidyr,
-    r3dmol, bio3d, shiny,
-    colorspace,
-    knitr,
-    rmarkdown,
-    testthat (>= 3.0.0)
+        BiocManager,
+        BiocGenerics,
+        GenomicRanges,
+        GenomeInfoDb,
+        AnnotationHub,
+        ensembldb,
+        httr,
+        tidyr,
+        r3dmol, bio3d, shiny, shiny.gosling,
+        colorspace,
+        knitr,
+        rmarkdown,
+        testthat (>= 3.0.0)
 biocViews: SNP, Annotation, FunctionalGenomics, StructuralPrediction,
-    Transcriptomics, VariantAnnotation, GenePrediction, ImmunoOncology
+        Transcriptomics, VariantAnnotation, GenePrediction, ImmunoOncology
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.1
+RoxygenNote: 7.3.2
 VignetteBuilder: knitr
 Config/testthat/edition: 3

NAMESPACE

@@ -17,6 +17,7 @@ export(db_disconnect_all)
 export(db_range_join)
 export(db_tables)
 export(db_temporary_table)
+export(plot_granges)
 export(to_GPos)
 importFrom(BiocBaseUtils,isCharacter)
 importFrom(BiocBaseUtils,isScalarCharacter)

R/plot_granges.R

@@ -0,0 +1,222 @@
+#' @rdname plot_granges
+#'
+#' @title Plot a GRanges object using Shiny and Gosling
+#'
+#' @description This function creates a Shiny app that displays a
+#'     Gosling plot of a given GRanges object.  It visualizes genomic
+#'     ranges with both rectangle and point representations, and
+#'     allows for customization of the plot title and subtitle.
+
+#' @details
+#' The function supports 2 types of plots as selected through the `plot_type` 
+#' argument: (1) a barplot-like view of the pathogenicity score at each position, 
+#' similar to a sequencing coverage plot, and (2) a lollipop plot focusing on 
+#' the pathogenicity classification (ambiguous, benign, pathogenic) at each 
+#' position. It requires that the [`GRanges`] object has the following metadata
+#' columns: 'am_class' (effect classification),'am_pathogenicity' 
+#' (pathogenicity score), 'ALT' (alternative allele) and 'REF' 
+#' (reference allele).
+
+#' @param gr A [`GRanges`] object containing the genomic ranges to
+#'     be plotted.
+#' @param title character(1) Title of the plot. Default is
+#'     "GRanges Plot".
+#' @param subtitle character(1) The subtitle of the plot. Default
+#'     is "Stacked nucleotide example".
+#' @param plot_type character(1) Select the type of gosling plot. 
+#' Default is "bars".
+#'     - "bars": Stacked bar plot with height based on pathogenicity score,
+#'     - "lollipop": variation of a bar chart where the bar is replaced with a 
+#'     line and a dot at the end to show mutation variations.
+#'
+#' @return A `shinyApp` object that, when run, displays the Gosling
+#'     plot.
+#'
+#' @note This function requires the `shiny`, `shiny.gosling`, and `GenomicRanges`
+#'     packages to be installed.
+#'
+#' @examples
+#' if (requireNamespace("GenomicRanges")) {
+#'
+#'    ## Create a sample GRanges object from AlphamissenseR
+#'    gpos <-
+#'        am_data("hg38") |>
+#'        filter(uniprot_id == "Q1W6H9") |>
+#'        to_GPos()
+#'
+#'    ## Plot the GRanges object
+#'     plot_granges(
+#'        gpos, mode = "bar", title = "Q1W6H_track",
+#'        subtitle = "bar plot example"
+#'     )
+#'}
+#'
+#'
+#'
+#' @export
+plot_granges <-
+    function(gr_input,
+             title = "GRanges Plot",
+             subtitle = "Stacked nucleotide example",
+             plot_type = "bars")
+{
+    ## Validate input
+    stopifnot(
+            is(granges, "GRanges"),
+            isScalarCharacter(title),
+            isScalarCharacter(subtitle),
+            isScalarCharacter(plot_type)
+        )
+
+    ## Define categories and color mapping
+    categories <- c("likely_benign", "ambiguous", "likely_pathogenic")
+    colormapping <- c("#89d5f5", "gray", "#f56c6c")
+
+    ## Turns out gr must be coerced to GRanges(), will look into this later
+    gr_input <- as(gr_input, "GRanges")
+    ## Get range from GRanges object
+    r <- range(gr_input)
+
+    # This fixes the bug if .gosling directory does not already exist
+    if (!dir.exists(".gosling")){
+        dir.create(".gosling")
+    }
+
+    ## Prepare track data
+    track_data <- shiny.gosling::track_data_gr(
+        gr_input,
+        chromosomeField = "seqnames",
+        genomicFields = c("start", "end")
+    )
+
+
+    ## trigger the option for bars or lollipop        
+    if (identical(plot_type, "bars")){
+        #define single track
+        track_bar <- shiny.gosling::add_single_track(
+            width = 800,
+            height = 180,
+            data = track_data,
+            mark = "bar",
+            x = shiny.gosling::visual_channel_x(
+                field = "start", type = "genomic", axis = "bottom"
+            ),
+            xe = shiny.gosling::visual_channel_x(field = "end", type = "genomic"),
+            y = shiny.gosling::visual_channel_y(
+                field = "am_pathogenicity", type = "quantitative", axis = "right"
+            ),
+            color = shiny.gosling::visual_channel_color(
+                field = "am_pathogenicity",
+                type = "quantitative"
+            ),
+            tooltip = shiny.gosling::visual_channel_tooltips(
+                shiny.gosling::visual_channel_tooltip(field = "REF", type = "nominal",
+                                       alt = "Reference"),
+                shiny.gosling::visual_channel_tooltip(field = "ALT", type = "nominal",
+                                       alt = "Alternative / Mutation"),
+                shiny.gosling::visual_channel_tooltip(
+                    field = "am_pathogenicity",
+                    type = "quantitative",
+                    alt = "AM_Pathogenicity Score",
+                    format = "0.2"
+                ) ),
+            size = list(value = 5)
+        )
+
+        composed_view <- shiny.gosling::compose_view(
+            layout = "linear",
+            xDomain = list(chromosome = as.character(seqnames(r)),
+                           interval = c(start(r), end(r))),
+            tracks = track_bar
+
+        )
+
+    ## other option    
+    } else if (identical(plot_type, "lollipop")){
+
+    ## Define multi tracks
+    track_ref <- shiny.gosling::add_single_track(
+        data = track_data,
+        mark = "rect",
+        x = shiny.gosling::visual_channel_x(field = "start", type = "genomic", axis = "top"),
+        xe = shiny.gosling::visual_channel_x(field = "end", type = "genomic"),
+        size = list(value = 50),
+        stroke = "lightgrey",
+        strokeWidth = list(value = 1),
+        opacity = list(value = 0.3)
+    )
+
+    track_alt <- shiny.gosling::add_single_track(
+        data = track_data,
+        mark = "point",
+        x = shiny.gosling::visual_channel_x(field = "start", type = "genomic", axis = "top"),
+        xe = shiny.gosling::visual_channel_x(field = "end", type = "genomic"),
+        y = shiny.gosling::visual_channel_y(field = "am_class", type="nominal", 
+                       domain= categories, axis = "left",baseline = "ambiguous" ),
+        text = list(field = "ALT", type = "nominal"),
+        size = list(value = 5),
+        tooltip = shiny.gosling::visual_channel_tooltips(
+            shiny.gosling::visual_channel_tooltip(field = "REF", type = "nominal",
+                                   alt = "Reference"),
+            shiny.gosling::visual_channel_tooltip(field = "ALT", type = "nominal",
+                                   alt = "Alternative / Mutation"),
+            shiny.gosling::visual_channel_tooltip(
+                field = "am_pathogenicity",
+                type = "quantitative",
+                alt = "AM_Pathogenicity Score",
+                format = "0.2"
+            ) )
+    )
+
+    ## Compose view
+    composed_view <- shiny.gosling::compose_view(
+        width = 800,
+        height = 180,
+        multi = TRUE,
+        layout = "linear",
+        xDomain = list(
+            chromosome = as.character(seqnames(r)),
+            interval = c(start(r), end(r))
+        ),
+        alignment = "overlay",
+        color = shiny.gosling::visual_channel_color(
+            field = "am_class",
+            type = "nominal",
+            domain = categories,
+            baseline = "ambiguous",
+            range = colormapping,
+            legend = TRUE
+        ),
+        tracks = shiny.gosling::add_multi_tracks(track_ref, track_alt)
+    )
+
+    } 
+    ## trigger check
+    else {
+        stop("Invalid plot_type. Use 'bars' or 'lollipop'")
+    }
+    ## Arrange into view
+    arranged_view3 <- shiny.gosling::arrange_views(
+        title = title,
+        subtitle = subtitle,
+        views = composed_view
+    )
+
+    ## Create Shiny app
+    ui <- shiny::fluidPage(
+        shiny.gosling::use_gosling(clear_files = FALSE),
+        shiny.gosling::goslingOutput("gosling_plot")
+    )
+
+    server <- function(input, output, session) {
+        output$gosling_plot <- shiny.gosling::renderGosling({
+            shiny.gosling::gosling(
+                component_id = "component_3",
+                arranged_view3
+            )
+        })
+    }
+
+    ## Return the Shiny app
+    shiny::shinyApp(ui, server)
+}