Write same-scale hires images for input to Fiji
Source:R/rescale_fiji_inputs.R
rescale_fiji_inputs.RdGiven a data.frame() of sample information (sample_info)
with
columns capture_area, group, and spaceranger_dir,
Write new high-resolution images for use as input to Fiji
https://imagej.net/software/fiji/. Particularly
when capture areas come from different slides, there is a risk of significant
scale differences among SpaceRanger's tissue_hires_image.png images;
that is, the physical distance represented by a pixel from each capture area
may differ nontrivially, leading to a distance-distorted output image, and
inconsistent scaling when later transforming pixel coordinates. This function
writes approximately high-res images whose pixels are of equal physical size
within each group, then adds intra_group_scalar and
group_hires_scalef columns to sample_info. intra_group_scalar
gives the scalar by a which a given capture area's
tissue_hires_image.png image and pixel
coordinates must be multiplied to match the scale of other group
members; group_hires_scalef gives the new tissue_hires_scalef
(as from SpaceRanger's scalefactors_json.json file) appropriate for
every capture area from the group.
Arguments
- sample_info
A
data.frame()with columnscapture_area,group,fiji_xml_path,fiji_image_path,spaceranger_dir,intra_group_scalar, andgroup_hires_scalef. The last two are made byrescale_fiji_inputs().- out_dir
A
character(1)vector giving a path to a directory to place the output images, which must exist in advance.
Value
A tibble: a copy of sample_info with
additional columns
intra_group_scalar and group_hires_scalef.
Examples
# Define sample information for the example human brain data
sample_info <- dplyr::tibble(
group = "Br2719",
capture_area = c("V13B23-283_A1", "V13B23-283_C1", "V13B23-283_D1")
)
# Add 'spaceranger_dir' column
sr_dir <- tempdir()
temp <- unzip(
spatialLIBD::fetch_data("visiumStitched_brain_spaceranger"),
exdir = sr_dir
)
#> 2024-10-24 20:16:55.189005 loading file /github/home/.cache/R/BiocFileCache/7603a007f35_visiumStitched_brain_spaceranger.zip%3Frlkey%3Dbdgjc6mgy1ierdad6h6v5g29c%26dl%3D1
sample_info$spaceranger_dir <- file.path(
sr_dir, sample_info$capture_area, "outs", "spatial"
)
# Add Fiji-output-related columns
fiji_dir <- tempdir()
temp <- unzip(
spatialLIBD::fetch_data("visiumStitched_brain_Fiji_out"),
exdir = fiji_dir
)
#> 2024-10-24 20:16:57.70092 loading file /github/home/.cache/R/BiocFileCache/76048672d76_visiumStitched_brain_fiji_out.zip%3Frlkey%3Dptwal8f5zxakzejwd0oqw0lhj%26dl%3D1
sample_info$fiji_xml_path <- temp[grep("xml$", temp)]
sample_info$fiji_image_path <- temp[grep("png$", temp)]
## Re-size images and add more information to the sample_info
out_dir <- tempdir()
sample_info_new <- rescale_fiji_inputs(sample_info, out_dir = out_dir)
# Scale factors are computed that are necessary downstream (i.e. with
# prep_fiji_*() functions)
sample_info_new[, setdiff(colnames(sample_info_new), colnames(sample_info))]
#> # A tibble: 3 × 2
#> intra_group_scalar group_hires_scalef
#> <dbl> <dbl>
#> 1 1.00 0.0825
#> 2 1.00 0.0825
#> 3 1 0.0825
# Image are produced that are ready for alignment in Fiji
list.files(out_dir)
#> [1] "Br2719"
#> [2] "Br2719.png"
#> [3] "Br2719.xml"
#> [4] "HDF5Array_dataset_creation_global_counter"
#> [5] "HDF5Array_dump"
#> [6] "HDF5Array_dump_log"
#> [7] "HDF5Array_dump_names_global_counter"
#> [8] "V13B23-283_A1"
#> [9] "V13B23-283_A1.png"
#> [10] "V13B23-283_C1"
#> [11] "V13B23-283_C1.png"
#> [12] "V13B23-283_D1"
#> [13] "V13B23-283_D1.png"
#> [14] "bslib-5ff8f344b905f9ef2a33199151429212"
#> [15] "downlit"
#> [16] "file363713b563ec"
#> [17] "file36373384864b"
#> [18] "file36373a2556b5"
#> [19] "file36374b3b5235"
#> [20] "file363755368c23"
#> [21] "file36377985d4b"