## ----include = [encoded data, 9983 characters]
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

options(width = 10000)

## ----fig-input-diagram, echo=FALSE, fig.align='center', out.width='75%'[encoded data, 9927 characters]
knitr::include_graphics("figures/input_diagram.png")

## ----fig-input-table, echo=FALSE, fig.align='center', out.width='75%'[encoded data, 9929 characters]
knitr::include_graphics("figures/input_table.png")

## ----brapa-data-kable, [encoded data, 9975 characters]
# Load a data frame from the sample data
b_rapa_data <- system.file("extdata/brapa_arabidopsis_data.csv", package = "greatR") |>
  data.table::fread()

b_rapa_data[, .SD[1:2], by = accession][, .(gene_id, accession, timepoint, expression_value, replicate)] |>
  knitr::kable()

## ----fig-input-list-tables, echo=FALSE, fig.align='center', out.width='85%'[encoded data, 9923 characters]
knitr::include_graphics("figures/input_list_tables.png")

## ----brapa-data-list-df-read, [encoded data, 9968 characters]
# Load a data frame from the sample data
brapa_ref_data <- system.file("extdata/brapa_SOC1_data.csv", package = "greatR") |>
  data.table::fread()

ara_query_data <- system.file("extdata/arabidopsis_SOC1_data.csv", package = "greatR") |>
  data.table::fread()

list_df <- list(
  reference = brapa_ref_data,
  query = ara_query_data
)

## ----fig-input-list-vectors, echo=FALSE, fig.align='center', out.width='38%'[encoded data, 9922 characters]
knitr::include_graphics("figures/input_list_vectors.png")

## [encoded data, 9997 characters]
# Define expression value vectors
ref_expressions <- c(1.9, 3.1, 7.8, 31.6, 33.7, 31.5, 131.4, 107.5, 116.7, 112.5, 109.7, 57.4, 50.9)
query_expressions <- c(14, 12.1, 15.9, 47, 30.9, 50.5, 80.1, 67.4, 72.9, 61.7)

list_vector <- list(
  reference = ref_expressions,
  query = query_expressions
)

list_vector

