`lancer` Example in Quarto

Author

Jeremy Selva

R Packages used

Code

library(lancer)
library(tibble)
library(reactable)
library(patchwork)
library(sessioninfo)
library(report)

Code

r_package_table <- sessioninfo::package_info()
rownames(r_package_table) <- NULL

r_package_table |>
  dplyr::mutate(
    version = ifelse(is.na(r_package_table$loadedversion), 
                     r_package_table$ondiskversion, 
                     r_package_table$loadedversion)
  ) |> 
  dplyr::filter(.data$attached == TRUE) |> 
  dplyr::select(c("package", "version", 
                  "date", "source"
    )
  ) |> 
  reactable::reactable(
    columns = list(
      package = reactable::colDef(
        # Freeze first column
        sticky = "left",
        style = list(borderRight = "1px solid #eee"),
        headerStyle = list(borderRight = "1px solid #eee"))
  )
  )

R Platform Information

Code

# Taken from https://github.com/r-lib/sessioninfo/issues/75
get_quarto_version <- function() {
  if (isNamespaceLoaded("quarto")) {
    path <- quarto::quarto_path()
    ver <- system("quarto -V", intern = TRUE)
    if (is.null(path)) {
      "NA (via quarto)"
    } else {
      paste0(ver, " @ ", path, "/ (via quarto)")
    }
  } else {
    path <- Sys.which("quarto")
    if (path == "") {
      "NA"
    } else {
      ver <- system("quarto -V", intern = TRUE)
      paste0(ver, " @ ", path)
    }
  }
}

r_platform_table <- sessioninfo::platform_info()
r_platform_table[["quarto"]] <- get_quarto_version()[1]

r_platform_table <- data.frame(
    setting = names(r_platform_table),
    value = unlist(r_platform_table,
                   use.names = FALSE),
    stringsAsFactors = FALSE
  )

r_platform_table |>
  reactable::reactable(
    defaultPageSize = 5
  )

Data creation

Code

concentration <- c(
  10, 20, 25, 40, 50, 60,
  75, 80, 100, 125, 150,
  10, 25, 40, 50, 60,
  75, 80, 100, 125, 150)

curve_batch_name <- c(
  "B1", "B1", "B1", "B1", "B1",
  "B1", "B1", "B1", "B1", "B1", "B1",
  "B2", "B2", "B2", "B2", "B2",
  "B2", "B2", "B2", "B2", "B2")

sample_name <- c(
  "Sample_010a", "Sample_020a", "Sample_025a",
  "Sample_040a", "Sample_050a", "Sample_060a",
  "Sample_075a", "Sample_080a", "Sample_100a",
  "Sample_125a", "Sample_150a",
  "Sample_010b", "Sample_025b",
  "Sample_040b", "Sample_050b", "Sample_060b",
  "Sample_075b", "Sample_080b", "Sample_100b",
  "Sample_125b", "Sample_150b")

curve_1_saturation_regime <- c(
  5748124, 16616414, 21702718, 36191617,
  49324541, 55618266, 66947588, 74964771,
  75438063, 91770737, 94692060,
  5192648, 16594991, 32507833, 46499896,
  55388856, 62505210, 62778078, 72158161,
  78044338, 86158414)

curve_2_good_linearity <- c(
  31538, 53709, 69990, 101977, 146436, 180960,
  232881, 283780, 298289, 344519, 430432,
  25463, 63387, 90624, 131274, 138069,
  205353, 202407, 260205, 292257, 367924)

curve_3_noise_regime <- c(
  544, 397, 829, 1437, 1808, 2231,
  3343, 2915, 5268, 8031, 11045,
  500, 903, 1267, 2031, 2100,
  3563, 4500, 5300, 8500, 10430)

curve_4_poor_linearity <- c(
  380519, 485372, 478770, 474467, 531640, 576301,
  501068, 550201, 515110, 499543, 474745,
  197417, 322846, 478398, 423174, 418577,
  426089, 413292, 450190, 415309, 457618)

curve_batch_annot <- tibble::tibble(
  Sample_Name = sample_name,
  Curve_Batch_Name = curve_batch_name,
  Concentration = concentration
)

curve_data <- tibble::tibble(
  Sample_Name = sample_name,
  `Curve_1` = curve_1_saturation_regime,
  `Curve_2` = curve_2_good_linearity,
  `Curve_3` = curve_3_noise_regime,
  `Curve_4` = curve_4_poor_linearity
)

Code

curve_batch_annot |> 
  reactable::reactable(
    defaultPageSize = 5,
    bordered = TRUE,
    highlight = TRUE,
    paginationType = "jump"
    )

Code

curve_data |> 
  reactable::reactable(
    defaultPageSize = 5,
    bordered = TRUE,
    highlight = TRUE,
    paginationType = "jump"
    )

Create curve table

Code

curve_table <- lancer::create_curve_table(
  curve_batch_annot, 
  curve_data,
  common_column = "Sample_Name",
  signal_var = "Signal",
  column_group = "Curve_Name"
)

Code

curve_table |> 
  reactable::reactable(
    defaultPageSize = 5,
    defaultColDef = reactable::colDef(
      minWidth = 200),
    bordered = TRUE,
    highlight = TRUE,
    paginationType = "jump"
)

Create curve statistical summary

Code

curve_summary <- lancer::summarise_curve_table(
  curve_table,
  grouping_variable = c("Curve_Name",
                        "Curve_Batch_Name"),
  conc_var = "Concentration",
  signal_var = "Signal")

curve_classified <- lancer::evaluate_linearity(
  curve_summary,
  grouping_variable = c("Curve_Name",
                        "Curve_Batch_Name"))

Code

curve_summary |> 
  reactable::reactable(
    defaultPageSize = 5,
    defaultColDef = reactable::colDef(
      minWidth = 200), 
    bordered = TRUE,
    highlight = TRUE,
    paginationType = "jump"
)

Code

curve_classified |> 
  reactable::reactable(
    defaultPageSize = 5,
    defaultColDef = reactable::colDef(
      minWidth = 200),
    bordered = TRUE,
    highlight = TRUE,
    paginationType = "jump"
)

Export results as Excel

Code

lancer::write_summary_excel(
  curve_classified, 
  file_name = "curve_summary.xlsx")

Export results as pdf

Code

ggplot_table <- lancer::add_ggplot_panel(
  curve_table,
  curve_summary = curve_classified,
  grouping_variable = c("Curve_Name",
                        "Curve_Batch_Name"),
  conc_var = "Concentration",
  signal_var = "Signal")

# Get the list of ggplot list for each group
ggplot_list <- ggplot_table$panel

lancer::view_ggplot_pdf(
  ggplot_list,
  filename = "curve_plot.pdf",
  ncol_per_page = 2,
  nrow_per_page = 2)

Code

patchwork::wrap_plots(
  ggplot_list,
  ncol = 2,
  nrow = 4
)

A display of dilution curves with summary statistics in ggplot.

Export results as trellis table

Code

trellis_table <- lancer::add_plotly_panel(
  curve_table,
  curve_summary = curve_classified,
  grouping_variable = c("Curve_Name",
                        "Curve_Batch_Name"),
  sample_name_var = "Sample_Name",
  curve_batch_var = "Curve_Batch_Name",
  curve_batch_col = c("#377eb8",
                      "#4daf4a"),
  conc_var = "Concentration",
  conc_var_units = "%",
  conc_var_interval = 50,
  signal_var = "Signal",
  have_plot_title = FALSE)

trellis_table <-  lancer::convert_to_cog(
  trellis_table,
  grouping_variable = c("Curve_Name",
                        "Curve_Batch_Name"),
  panel_variable = "panel",
  col_name_vec = "col_name_vec",
  desc_vec = "desc_vec",
  type_vec = "type_vec"
  )

# Pressing Render button will not create the 
# index.html file (Though it is not needed)
# Call this function via console to create index.html file
lancer::view_trellis_html(
  trellis_table,
  grouping_variable = c("Curve_Name",
                        "Curve_Batch_Name"),
  trellis_report_name = "Curve_Plot",
  trellis_report_folder = "Curve_Plot_Folder")

R Package Reference

Code

report::cite_packages() |> 
  suppressWarnings()

Lin G (2023). reactable: Interactive Data Tables for R. R packageversion 0.4.3, https://CRAN.R-project.org/package=reactable.
Makowski D, Ben-Shachar M, Patil I, Lüdecke D (2021). “AutomatedResults Reporting as a Practical Tool to Improve Reproducibility andMethodological Best Practices Adoption.” CRAN.https://github.com/easystats/report.
Müller K, Wickham H (2022). tibble: Simple Data Frames. R packageversion 3.1.8, https://CRAN.R-project.org/package=tibble.
Pedersen T (2022). patchwork: The Composer of Plots. R packageversion 1.1.2, https://CRAN.R-project.org/package=patchwork.
R Core Team (2022). R: A Language and Environment for StatisticalComputing. R Foundation for Statistical Computing, Vienna, Austria.https://www.R-project.org/.
Selva J, Torta F, Burla B, Wenk M (2023). lancer: Linearity Assessmentand Curve Explorer. https://slinghub.github.io/lancer/,https://github.com/SLINGhub/lancer.
Wickham H, Chang W, Flight R, Müller K, Hester J (2021). sessioninfo:R Session Information. R package version 1.2.2,https://CRAN.R-project.org/package=sessioninfo.

--- title: "`lancer` Example in Quarto" author: "Jeremy Selva" format: html: theme: light: cerulean dark: cyborg toc: true toc-depth: 3 toc-location: left number-sections: false code-fold: show code-overflow: scroll code-copy: true code-tools: true code-link: true self-contained: false smooth-scroll: true --- # R Packages used ```{r R Packages used} library(lancer) library(tibble) library(reactable) library(patchwork) library(sessioninfo) library(report) ``` ```{r See packages info} #| code-fold: true r_package_table <- sessioninfo::package_info() rownames(r_package_table) <- NULL r_package_table |> dplyr::mutate( version = ifelse(is.na(r_package_table$loadedversion), r_package_table$ondiskversion, r_package_table$loadedversion) ) |> dplyr::filter(.data$attached == TRUE) |> dplyr::select(c("package", "version", "date", "source" ) ) |> reactable::reactable( columns = list( package = reactable::colDef( # Freeze first column sticky = "left", style = list(borderRight = "1px solid #eee"), headerStyle = list(borderRight = "1px solid #eee")) ) ) ``` # R Platform Information ```{r See session info} #| code-fold: true # Taken from https://github.com/r-lib/sessioninfo/issues/75 get_quarto_version <- function() { if (isNamespaceLoaded("quarto")) { path <- quarto::quarto_path() ver <- system("quarto -V", intern = TRUE) if (is.null(path)) { "NA (via quarto)" } else { paste0(ver, " @ ", path, "/ (via quarto)") } } else { path <- Sys.which("quarto") if (path == "") { "NA" } else { ver <- system("quarto -V", intern = TRUE) paste0(ver, " @ ", path) } } } r_platform_table <- sessioninfo::platform_info() r_platform_table[["quarto"]] <- get_quarto_version()[1] r_platform_table <- data.frame( setting = names(r_platform_table), value = unlist(r_platform_table, use.names = FALSE), stringsAsFactors = FALSE ) r_platform_table |> reactable::reactable( defaultPageSize = 5 ) ``` # Data creation ```{r Data creation} concentration <- c( 10, 20, 25, 40, 50, 60, 75, 80, 100, 125, 150, 10, 25, 40, 50, 60, 75, 80, 100, 125, 150) curve_batch_name <- c( "B1", "B1", "B1", "B1", "B1", "B1", "B1", "B1", "B1", "B1", "B1", "B2", "B2", "B2", "B2", "B2", "B2", "B2", "B2", "B2", "B2") sample_name <- c( "Sample_010a", "Sample_020a", "Sample_025a", "Sample_040a", "Sample_050a", "Sample_060a", "Sample_075a", "Sample_080a", "Sample_100a", "Sample_125a", "Sample_150a", "Sample_010b", "Sample_025b", "Sample_040b", "Sample_050b", "Sample_060b", "Sample_075b", "Sample_080b", "Sample_100b", "Sample_125b", "Sample_150b") curve_1_saturation_regime <- c( 5748124, 16616414, 21702718, 36191617, 49324541, 55618266, 66947588, 74964771, 75438063, 91770737, 94692060, 5192648, 16594991, 32507833, 46499896, 55388856, 62505210, 62778078, 72158161, 78044338, 86158414) curve_2_good_linearity <- c( 31538, 53709, 69990, 101977, 146436, 180960, 232881, 283780, 298289, 344519, 430432, 25463, 63387, 90624, 131274, 138069, 205353, 202407, 260205, 292257, 367924) curve_3_noise_regime <- c( 544, 397, 829, 1437, 1808, 2231, 3343, 2915, 5268, 8031, 11045, 500, 903, 1267, 2031, 2100, 3563, 4500, 5300, 8500, 10430) curve_4_poor_linearity <- c( 380519, 485372, 478770, 474467, 531640, 576301, 501068, 550201, 515110, 499543, 474745, 197417, 322846, 478398, 423174, 418577, 426089, 413292, 450190, 415309, 457618) curve_batch_annot <- tibble::tibble( Sample_Name = sample_name, Curve_Batch_Name = curve_batch_name, Concentration = concentration ) curve_data <- tibble::tibble( Sample_Name = sample_name, `Curve_1` = curve_1_saturation_regime, `Curve_2` = curve_2_good_linearity, `Curve_3` = curve_3_noise_regime, `Curve_4` = curve_4_poor_linearity ) ``` ```{r View curve_batch_annot} curve_batch_annot |> reactable::reactable( defaultPageSize = 5, bordered = TRUE, highlight = TRUE, paginationType = "jump" ) ``` ```{r View curve_data} curve_data |> reactable::reactable( defaultPageSize = 5, bordered = TRUE, highlight = TRUE, paginationType = "jump" ) ``` # Create curve table ```{r Create curve_table} curve_table <- lancer::create_curve_table( curve_batch_annot, curve_data, common_column = "Sample_Name", signal_var = "Signal", column_group = "Curve_Name" ) ``` ```{r View curve_table} curve_table |> reactable::reactable( defaultPageSize = 5, defaultColDef = reactable::colDef( minWidth = 200), bordered = TRUE, highlight = TRUE, paginationType = "jump" ) ``` # Create curve statistical summary ```{r Create curve statistical summary} curve_summary <- lancer::summarise_curve_table( curve_table, grouping_variable = c("Curve_Name", "Curve_Batch_Name"), conc_var = "Concentration", signal_var = "Signal") curve_classified <- lancer::evaluate_linearity( curve_summary, grouping_variable = c("Curve_Name", "Curve_Batch_Name")) ``` ```{r View curve_summary} curve_summary |> reactable::reactable( defaultPageSize = 5, defaultColDef = reactable::colDef( minWidth = 200), bordered = TRUE, highlight = TRUE, paginationType = "jump" ) ``` ```{r View curve_classified} curve_classified |> reactable::reactable( defaultPageSize = 5, defaultColDef = reactable::colDef( minWidth = 200), bordered = TRUE, highlight = TRUE, paginationType = "jump" ) ``` # Export results as Excel ```{r Export results as Excel} lancer::write_summary_excel( curve_classified, file_name = "curve_summary.xlsx") ``` # Export results as pdf ```{r Export results as pdf} ggplot_table <- lancer::add_ggplot_panel( curve_table, curve_summary = curve_classified, grouping_variable = c("Curve_Name", "Curve_Batch_Name"), conc_var = "Concentration", signal_var = "Signal") # Get the list of ggplot list for each group ggplot_list <- ggplot_table$panel lancer::view_ggplot_pdf( ggplot_list, filename = "curve_plot.pdf", ncol_per_page = 2, nrow_per_page = 2) ``` ```{r View ggplot_list} #| fig-width: 15 #| fig-height: 20 #| fig-alt: "A display of dilution curves with summary statistics in ggplot." #| column: screen-inset-right patchwork::wrap_plots( ggplot_list, ncol = 2, nrow = 4 ) ``` # Export results as trellis table ```{r Export results as trellis table} #| column: screen-inset-right trellis_table <- lancer::add_plotly_panel( curve_table, curve_summary = curve_classified, grouping_variable = c("Curve_Name", "Curve_Batch_Name"), sample_name_var = "Sample_Name", curve_batch_var = "Curve_Batch_Name", curve_batch_col = c("#377eb8", "#4daf4a"), conc_var = "Concentration", conc_var_units = "%", conc_var_interval = 50, signal_var = "Signal", have_plot_title = FALSE) trellis_table <- lancer::convert_to_cog( trellis_table, grouping_variable = c("Curve_Name", "Curve_Batch_Name"), panel_variable = "panel", col_name_vec = "col_name_vec", desc_vec = "desc_vec", type_vec = "type_vec" ) # Pressing Render button will not create the # index.html file (Though it is not needed) # Call this function via console to create index.html file lancer::view_trellis_html( trellis_table, grouping_variable = c("Curve_Name", "Curve_Batch_Name"), trellis_report_name = "Curve_Plot", trellis_report_folder = "Curve_Plot_Folder") ``` # R Package Reference ```{r package references} #| code-fold: true #| output: asis report::cite_packages() |> suppressWarnings() ```