13954380607
commented
2 months ago Open 13954380607 opened 2 months ago
13954380607
commented
2 months ago 
jiajic
commented
2 months ago Hi, could you provide any more details about the dataset used and what value is stored in the image_name variable?
It doesn't look like the following error is from code directly in Giotto (maybe it's part of some package we use for reading things in), so it's hard to figure out what's going on.
Error in if (file == "") stdin() else file(file) :
the condition has length > 1Not sure if the dataset you were using was the publicly available Visium Mouse Kidney dataset, but I tested the following calls and was not able to reproduce an error.
p <- "/Users/george/Library/CloudStorage/GoogleDrive-jiajic@bu.edu/Shared drives/Dries_lab/Datasets/Public_data/Spatial/Sequencing/Visium/Visium_Mouse_Kidney_data"
g <- createGiottoVisiumObject(visium_dir = p)
g <- createGiottoVisiumObject(visium_dir = p, expr_data = "raw")
g <- createGiottoVisiumObject(visium_dir = p, expr_data = "raw", gene_column_index = 2)
g <- createGiottoVisiumObject(visium_dir = p, expr_data = "raw", gene_column_index = 2, png_name = "tissue_hires_image.png")
spatPlot2D(g, show_image = T, point_alpha = 0.5)> sessionInfo()
R version 4.4.0 (2024-04-24)
Platform: aarch64-apple-darwin20
Running under: macOS Sonoma 14.4
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: America/New_York
tzcode source: internal
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] Giotto_4.1.0 GiottoClass_0.3.4
loaded via a namespace (and not attached):
[1] colorRamp2_0.1.0 DBI_1.2.2 MAST_1.30.0 deldir_2.0-4
[5] rlang_1.1.4 magrittr_2.0.3 GiottoUtils_0.1.10 matrixStats_1.3.0
[9] compiler_4.4.0 png_0.1-8 vctrs_0.6.5 reshape2_1.4.4
[13] stringr_1.5.1 pkgconfig_2.0.3 SpatialExperiment_1.14.0 crayon_1.5.2
[17] fastmap_1.2.0 backports_1.5.0 magick_2.8.4 XVector_0.44.0
[21] labeling_0.4.3 utf8_1.2.4 UCSC.utils_1.0.0 purrr_1.0.2
[25] bit_4.0.5 zlibbioc_1.50.0 GenomeInfoDb_1.40.0 jsonlite_1.8.8
[29] DelayedArray_0.30.0 terra_1.7-78 parallel_4.4.0 R6_2.5.1
[33] stringi_1.8.4 RColorBrewer_1.1-3 limma_3.60.0 reticulate_1.38.0
[37] GenomicRanges_1.56.0 scattermore_1.2 Rcpp_1.0.13 assertthat_0.2.1
[41] SummarizedExperiment_1.34.0 R.utils_2.12.3 IRanges_2.38.0 Matrix_1.7-0
[45] igraph_2.0.3 tidyselect_1.2.1 rstudioapi_0.16.0 abind_1.4-5
[49] codetools_0.2-20 lattice_0.22-6 tibble_3.2.1 intervals_0.15.4
[53] plyr_1.8.9 Biobase_2.64.0 withr_3.0.0 pillar_1.9.0
[57] MatrixGenerics_1.16.0 checkmate_2.3.1 stats4_4.4.0 plotly_4.10.4
[61] generics_0.1.3 dbscan_1.2-0 sp_2.1-4 S4Vectors_0.42.0
[65] ggplot2_3.5.1 munsell_0.5.1 scales_1.3.0 GiottoData_0.2.14
[69] gtools_3.9.5 multinet_4.1.2 glue_1.7.0 lazyeval_0.2.2
[73] tools_4.4.0 GiottoVisuals_0.2.4 data.table_1.15.4 cowplot_1.1.3
[77] grid_4.4.0 tidyr_1.3.1 colorspace_2.1-0 SingleCellExperiment_1.26.0
[81] GenomeInfoDbData_1.2.12 cli_3.6.3 fansi_1.0.6 S4Arrays_1.4.0
[85] viridisLite_0.4.2 arrow_16.1.0 dplyr_1.1.4 gtable_0.3.5
[89] R.methodsS3_1.8.2 digest_0.6.35 progressr_0.14.0 BiocGenerics_0.50.0
[93] SparseArray_1.4.1 ggrepel_0.9.5 rjson_0.2.21 htmlwidgets_1.6.4
[97] farver_2.1.2 R.oo_1.26.0 htmltools_0.5.8.1 lifecycle_1.0.4
[101] httr_1.4.7 statmod_1.5.0 bit64_4.0.5 Thank you so much! Sorry for the confusion, but now it gives me this message: Error in file == "" : comparison (==) is possible only for atomic and list types
13954380607
commented
2 months ago The dataset I used was the publicly available Visium Mouse Kidney dataset, but one thing I don't know is the structure of the dataset, like which files in which fold. Thank you!
13954380607
commented
2 months ago visium_kidney = createGiottoVisiumObject(visium_dir = data_path,
I don't know why it always gave me this error message. Thank you!
jiajic
commented
2 months ago The only things that really matter are that you have the spatial folder and also the expression matrix you want to use unzipped.
My directory looks like this:
> fs::dir_tree(p)
/Users/george/Library/CloudStorage/GoogleDrive-jiajic@bu.edu/Shared drives/Dries_lab/Datasets/Public_data/Spatial/Sequencing/Visium/Visium_Mouse_Kidney_data
├── V1_Mouse_Kidney_image.tif
├── V1_Mouse_Kidney_metrics_summary.csv
├── V1_Mouse_Kidney_raw_feature_bc_matrix.tar.gz
├── analysis
│ ├── clustering
│ │ ├── graphclust
│ │ │ └── clusters.csv
│ │ ├── kmeans_10_clusters
│ │ │ └── clusters.csv
│ │ ├── kmeans_2_clusters
│ │ │ └── clusters.csv
│ │ ├── kmeans_3_clusters
│ │ │ └── clusters.csv
│ │ ├── kmeans_4_clusters
│ │ │ └── clusters.csv
│ │ ├── kmeans_5_clusters
│ │ │ └── clusters.csv
│ │ ├── kmeans_6_clusters
│ │ │ └── clusters.csv
│ │ ├── kmeans_7_clusters
│ │ │ └── clusters.csv
│ │ ├── kmeans_8_clusters
│ │ │ └── clusters.csv
│ │ └── kmeans_9_clusters
│ │ └── clusters.csv
│ ├── diffexp
│ │ ├── graphclust
│ │ │ └── differential_expression.csv
│ │ ├── kmeans_10_clusters
│ │ │ └── differential_expression.csv
│ │ ├── kmeans_2_clusters
│ │ │ └── differential_expression.csv
│ │ ├── kmeans_3_clusters
│ │ │ └── differential_expression.csv
│ │ ├── kmeans_4_clusters
│ │ │ └── differential_expression.csv
│ │ ├── kmeans_5_clusters
│ │ │ └── differential_expression.csv
│ │ ├── kmeans_6_clusters
│ │ │ └── differential_expression.csv
│ │ ├── kmeans_7_clusters
│ │ │ └── differential_expression.csv
│ │ ├── kmeans_8_clusters
│ │ │ └── differential_expression.csv
│ │ └── kmeans_9_clusters
│ │ └── differential_expression.csv
│ ├── pca
│ │ └── 10_components
│ │ ├── components.csv
│ │ ├── dispersion.csv
│ │ ├── features_selected.csv
│ │ ├── projection.csv
│ │ └── variance.csv
│ ├── tsne
│ │ └── 2_components
│ │ └── projection.csv
│ └── umap
│ └── 2_components
│ └── projection.csv
├── filtered_feature_bc_matrix
│ ├── barcodes.tsv.gz
│ ├── features.tsv.gz
│ └── matrix.mtx.gz
├── raw_feature_bc_matrix
│ ├── barcodes.tsv.gz
│ ├── features.tsv.gz
│ └── matrix.mtx.gz
└── spatial
├── aligned_fiducials.jpg
├── detected_tissue_image.jpg
├── scalefactors_json.json
├── tissue_hires_image.png
├── tissue_lowres_image.png
└── tissue_positions_list.csvThank you, also my image name is: image_name = 'tissue_lowres_image.png', is this correct?
jiajic
commented
2 months ago Yes that should work. I just ran the following and it also worked
> g <- createGiottoVisiumObject(visium_dir = p, expr_data = "raw", gene_column_index = 2, png_name = "tissue_lowres_image.png")
A structured visium directory will be used
- found image
- found scalefactors. attempting automatic alignment for the 'lowres' image
a giotto python environment was found
Using python path:
"/Users/george/Library/r-miniconda-arm64/envs/giotto_env/bin/pythonw"
> g
An object of class giotto
>Active spat_unit: cell
>Active feat_type: rna
[SUBCELLULAR INFO]
polygons : cell
[AGGREGATE INFO]
expression -----------------------
[cell][rna] raw
spatial locations ----------------
[cell] raw
attached images ------------------
images : image
Use objHistory() to see steps and params used
> spatPlot2D(g, show_image = T, point_alpha = 0.5)
> g@images$image
An object of class giottoLargeImage : "image"
Image extent : 0, 11300.00002825, -11300.00002825, 0 (xmin, xmax, ymin, ymax)
Original image extent : 0, 11300.00002825, -11300.00002825, 0 (xmin, xmax, ymin, ymax)
Scale factor : 18.8333333804167, 18.8333333804167 (x, y)
Resolution : 0.053097345, 0.053097345 (x, y)
Layers : 3
Estimated max intensity : 174
Estimated min intensity : 17
Values : integers
File path : '/Users/george/Library/CloudStorage/GoogleDrive-jiajic@bu.edu/Shared drives/Dries_lab/Datasets/Public_data/Spatial/Sequencing/Visium/Visium_Mouse_Kidney_data/spatial//tissue_lowres_image.png'Not that the giottoLargeImage is indeed pointing to the tissue_lowres_image.png since that's the png_name asked for.
jiajic
commented
2 months ago visium_kidney = createGiottoVisiumObject(visium_dir = data_path, expr_data = data_path_F2_h5,
Oh wait it looks like you are using the h5 expression instead of the zipped folder with .mtx files. Please use the h5 params instead if you are using the .h5 expression information.
h5_visium_path = NULL,
h5_gene_ids = c("symbols", "ensembl"),
h5_tissue_positions_path = NULL,
h5_image_png_path = NULL,
h5_json_scalefactors_path = NULL,data_path = '/home/dl2373/new/'
fs::dir_tree(data_path) /home/dl2373/new/ ├── raw_feature_bc_matrix │ ├── barcodes.tsv │ ├── features.tsv │ ├── matrix.mtx │ ├── raw_feature_bc_matrix │ └── raw_feature_bc_matrix.h5 ├── spatial │ ├── scalefactors_json.json │ │ └── tissue_lowres_image.png │ └── tissue_lowres_image.png │ └── scalefactors_json.json └── tissue_positions_list.csv
Is this directory correct?
13954380607
commented
2 months ago library(Giotto)
results_folder = '/home/dl2373/new'
python_path = NULL instrs = createGiottoInstructions(save_dir = results_folder, save_plot = TRUE, show_plot = FALSE, python_path = python_path)
data_path = '/home/dl2373/new/' fs::dir_tree(data_path) image_name = 'tissue_lowres_image.png'
visium_kidney = createGiottoVisiumObject( visium_dir = data_path, expr_data = 'raw', png_name = image_name, gene_column_index = 2, instructions = instrs ) This is my full code. Thank you!
jiajic
commented
2 months ago That directory and code do look mostly correct.
I'm not sure why inside of raw_feature_bc_matrix, you have these extra files.
raw_feature_bc_matrix
raw_feature_bc_matrix.h5For the code, I would just suggest that results be a different folder than the data folder so that things don't get messy.
I ran your code and it worked on my side. It's pretty rare but maybe they have changed something with the output somehow since we last downloaded this dataset? I can try downloading a fresh copy and trying again in the morning if it's still not working for you.