README.md

In martinjhnhadley/gene.alignment.tables: Interactive Gene Alignment Visualisations for Shiny Apps

gene.alignment.tables

This package allows for interactive gene sequence alignment visualisations to be embedded into Shiny apps. An example Shiny app is provided in this package and available using runExample, please note that at present the output will only work within a Shiny app - future support to output as a htmlwidget might be possible...

runExample()

Installation

You can install gene.alignment.tables from github with:

# install.packages("devtools")
devtools::install_github("charliejhadley/gene.alignment.tables")

It's unlikely this package will live on CRAN, if it ever does there will be significant changes to the packages before deployment.

Example

The package comes with two example datasets, both of these are based on real research datasets but anonymised (for the time being).

# library("gene.alignment.tables")
str(hbv_long_s_sequence)
#> Classes 'tbl_df', 'tbl' and 'data.frame':    300 obs. of  4 variables:
#>  $ position : int  1 2 3 4 5 6 7 8 9 10 ...
#>  $ reference: chr  "W" "R" "Y" "Q" ...
#>  $ genome.a : chr  "-" "-" "-" "-" ...
#>  $ colour   : chr  "#f9fd74" "#ccfecc" NA "#bdd7ee" ...
str(hbv_pol_sequence)
#> Classes 'tbl_df', 'tbl' and 'data.frame':    843 obs. of  4 variables:
#>  $ position : int  1 2 3 4 5 6 7 8 9 10 ...
#>  $ reference: chr  "S" "C" "E" "S" ...
#>  $ genome.a : chr  "-" "-" "-" "-" ...
#>  $ colour   : chr  "#f4b084" "#bdd7ee" "#f4b084" "#fe6600" ...

To use visualise your own data you must have the following columns, any other columns will be displayed in the gene.tables.alignment viz.

| position | colour | |:--------:|:----------:| | 1 | "#f9fd74" | | 2 | "#f9fd74" |

You must also ensure to create the following observer and reactiveValues object in your server.R file:

selected_col_values <- reactiveValues()

  observe({
    if (!is.null(input[[paste0(alignment.dt.unique.id,
                               "_1_",
                               table_width,
                               "_rows_current")]])) {
      selected_col_values[["previous"]] <-
        isolate(selected_col_values[["current"]])

      all_inputs <- isolate(reactiveValuesToList(input))

      inputs_selected_cols <-
        grepl(
          paste0(
            alignment.dt.unique.id,
            "_[0-9]{1,}_[0-9]{1,}_columns_selected"
          ),
          names(all_inputs)
        )

      inputs_with_nulls <- all_inputs[inputs_selected_cols]

      inputs_selected_cols <-
        setNames(inputs_with_nulls, names(all_inputs)[inputs_selected_cols])

      selected_positions <-
        lapply(names(inputs_selected_cols), function(id) {
          id_to_sequence_position(id, shiny.input = input)
        }) %>%
        unlist()

      selected_positions


    } else {
      if (is.null(selected_col_values[["current"]])){
        selected_positions <- NULL
      }
      else {
        selected_positions <- selected_col_values[["current"]]
      }
    }

    selected_col_values[["current"]] <- selected_positions
  })

The selection of the sequence elements can be watched as follows:

selected_positions <- selected_col_values[["current"]] %>%
      sort()

martinjhnhadley/gene.alignment.tables documentation built on June 19, 2022, 11:56 a.m.