## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
    collapse = TRUE,
    comment = "#>",
    crop = NULL ## Related to https://stat.ethz.ch/pipermail/bioc-devel/2020-April/016656.html
)

## ----vignetteSetup, echo=FALSE, message=FALSE, warning = FALSE----------------
## Bib setup
library("RefManageR")

## Write bibliography information
bib <- c(
    R = citation(),
    BiocFileCache = citation("BiocFileCache")[1],
    BiocStyle = citation("BiocStyle")[1],
    dplyr = citation("dplyr")[1],
    DropletUtils = citation("DropletUtils")[1],
    ggplot2 = citation("ggplot2")[1],
    imager = citation("imager")[1],
    knitr = citation("knitr")[1],
    pkgcond = citation("pkgcond")[1],
    readr = citation("readr")[1],
    RefManageR = citation("RefManageR")[1],
    rjson = citation("rjson")[1],
    rmarkdown = citation("rmarkdown")[1],
    S4Vectors = citation("S4Vectors")[1],
    sessioninfo = citation("sessioninfo")[1],
    Seurat = citation("Seurat")[1],
    SpatialExperiment = citation("SpatialExperiment")[1],
    spatialLIBD = citation("spatialLIBD")[1],
    stringr = citation("stringr")[1],
    SummarizedExperiment = citation("SummarizedExperiment")[1],
    testthat = citation("testthat")[1],
    visiumStitched = citation("visiumStitched")[1],
    xml2 = citation("xml2")[1]
)

## ----"install", eval = FALSE--------------------------------------------------
# if (!requireNamespace("BiocManager", quietly = TRUE)) {
#     install.packages("BiocManager")
# }
# 
# BiocManager::install("visiumStitched")

## ----"citation"---------------------------------------------------------------
## Citation info
citation("visiumStitched")

## ----"start", message=FALSE, warning=FALSE------------------------------------
library("SpatialExperiment")
library("visiumStitched")
library("dplyr")
library("spatialLIBD")
library("BiocFileCache")
library("ggplot2")

## ----"sample_info"------------------------------------------------------------
## Create initial sample_info
sample_info <- data.frame(
    group = "Br2719",
    capture_area = c("V13B23-283_A1", "V13B23-283_C1", "V13B23-283_D1")
)

## Initial sample_info
sample_info

## ----"spaceranger_dir"--------------------------------------------------------
## Download example SpaceRanger output files
sr_dir <- tempdir()
temp <- unzip(spatialLIBD::fetch_data("visiumStitched_brain_spaceranger"),
    exdir = sr_dir
)
sample_info$spaceranger_dir <- file.path(
    sr_dir, sample_info$capture_area, "outs", "spatial"
)

## Sample_info with paths to SpaceRanger output directories
sample_info

## ----"rescale_inputs"---------------------------------------------------------
#   Generate rescaled approximately high-resolution images
sample_info <- rescale_fiji_inputs(sample_info, out_dir = tempdir())

## Sample_info with output directories
sample_info

## ----"fiji_out"---------------------------------------------------------------
fiji_dir <- tempdir()
temp <- unzip(fetch_data("visiumStitched_brain_Fiji_out"), exdir = fiji_dir)
sample_info$fiji_xml_path <- temp[grep("xml$", temp)]
sample_info$fiji_image_path <- temp[grep("png$", temp)]

## ----"print_info"-------------------------------------------------------------
## Complete sample_info
sample_info

## ----"prep_fiji"--------------------------------------------------------------
## Prepare the Fiji coordinates and images.
## These functions return the file paths to the newly-created files that follow
## the standard directory structure from SpaceRanger (10x Genomics)
spe_input_dir <- tempdir()
prep_fiji_coords(sample_info, out_dir = spe_input_dir)
prep_fiji_image(sample_info, out_dir = spe_input_dir)

## ----"gtf"--------------------------------------------------------------------
## Download the Gencode v32 GTF file which is the closest one to the one
## that was used with SpaceRanger. Note that SpaceRanger GTFs are available at
## https://cf.10xgenomics.com/supp/cell-exp/refdata-gex-GRCh38-2024-A.tar.gz
## but is too large for us to download here since it includes many other files
## we don't need right now.
## However, ideally you would adapt this code and use the actual GTF file you
## used when running SpaceRanger.
bfc <- BiocFileCache::BiocFileCache()
gtf_cache <- bfcrpath(
    bfc,
    paste0(
        "ftp://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/",
        "release_32/gencode.v32.annotation.gtf.gz"
    )
)

## ----"build_SpatialExperiment"------------------------------------------------
## Now we can build the SpatialExperiment object. We'll later explore error
## metrics related to computing new array coordinates, and thus specify
## 'calc_error_metrics = TRUE'.
spe <- build_SpatialExperiment(
    sample_info,
    coords_dir = spe_input_dir, reference_gtf = gtf_cache,
    calc_error_metrics = TRUE
)

## The images in this example data have to be mirrored across the horizontal axis.
spe <- SpatialExperiment::mirrorObject(spe, axis = "h")

## Explore stitched spe object
spe

## ----"exclude_overlapping"----------------------------------------------------
## Examine spots to exclude for plotting
table(spe$exclude_overlapping)

## ----"explore_coords", fig.height = 4-----------------------------------------
## Show combined raw expression of white-matter marker genes
wm_genes <- rownames(spe)[
    match(c("MBP", "GFAP", "PLP1", "AQP4"), rowData(spe)$gene_name)
]
vis_gene(spe, geneid = wm_genes, assayname = "counts", is_stitched = TRUE)

## ----"array_plot_orig"--------------------------------------------------------
## Plot positions of default array coordinates, before overwriting with more
## meaningful values. Use custom colors for each capture area
ca_colors <- c("#A33B20", "#e7bb41", "#3d3b8e")
names(ca_colors) <- c("V13B23-283_C1", "V13B23-283_D1", "V13B23-283_A1")

colData(spe) |>
    as_tibble() |>
    filter(in_tissue) |>
    ggplot(
        mapping = aes(
            x = array_row_original, y = array_col_original, color = capture_area
        )
    ) +
    geom_point(alpha = 0.3) +
    scale_color_manual(values = ca_colors)

## ----"array_plot_after"-------------------------------------------------------
## Plot positions of redefined array coordinates
colData(spe) |>
    as_tibble() |>
    filter(in_tissue) |>
    ggplot(
        mapping = aes(
            x = array_row, y = array_col, color = capture_area
        )
    ) +
    geom_point(alpha = 0.3) +
    scale_color_manual(values = ca_colors)

## ----"euclidean_error"--------------------------------------------------------
#   Explore the distribution of Euclidean error
colData(spe) |>
    as_tibble() |>
    ggplot(mapping = aes(x = 0, y = euclidean_error)) +
    geom_boxplot()

## ----"shared_neighbors"-------------------------------------------------------
#   Explore the distribution of Euclidean error
colData(spe) |>
    as_tibble() |>
    ggplot(mapping = aes(x = 0, y = shared_neighbors)) +
    geom_boxplot()

## ----"precast_k2_stitched", fig.height = 4------------------------------------
## Grab SpatialExperiment with normalized counts
spe_norm <- fetch_data(type = "visiumStitched_brain_spe")
assayNames(spe_norm)

## PRECAST k = 2 clusters with our manually chosen colors
vis_clus(
    spe_norm,
    clustervar = "precast_k2_stitched",
    is_stitched = TRUE,
    colors = c(
        "1" = "gold",
        "2" = "darkblue",
        "NA" = "white"
    ),
    spatial = FALSE
)

## ----"precast_k4_stitched", fig.height = 4------------------------------------
## PRECAST results already available in this example data
vars <- colnames(colData(spe_norm))
vars[grep("precast", vars)]

## PRECAST k = 4 clusters with default cluster colors
vis_clus(
    spe_norm,
    clustervar = "precast_k4_stitched",
    is_stitched = TRUE,
    spatial = FALSE
)

## ----createVignette, eval=FALSE-----------------------------------------------
# ## Create the vignette
# library("rmarkdown")
# system.time(render("visiumStitched.Rmd", "BiocStyle::html_document"))
# 
# ## Extract the R code
# library("knitr")
# knit("visiumStitched.Rmd", tangle = TRUE)

## ----reproduce3, echo=FALSE-------------------------------------------------------------------------------------------
## Session info
library("sessioninfo")
options(width = 120)
session_info()

## ----vignetteBiblio, results = "asis", echo = FALSE, warning = FALSE, message = FALSE---------------------------------
## Print bibliography
PrintBibliography(bib, .opts = list(hyperlink = "to.doc", style = "html"))