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Vizgen MERSCOPE Starter Tutorial

Input Data

The input is a SGE dataset from the adult mouse hippocampus, extracted by masking a coronal brain section (Slice Number: 2;Replicate Number: 1; file: detected_transcripts.csv) from Vizgen MERSCOPE Neuroscience Showcase.

File Format

The MERSCOPE input SGE includes one comma‑delimited text file in the following format:

CSV File Format

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,barcode_id,global_x,global_y,global_z,x,y,fov,gene
0,22,56.930107,3851.851,5.0,147.80061,1711.9067,0,Adgre1
1,22,183.60107,3874.0085,5.0,1320.6799,1917.0692,0,Adgre1
2,22,59.750736,3666.5576,5.0,132.66754,1844.2372,1,Adgre1
  • Column 1: Unique numeric index for each transcript within a field of view (non-consecutive, ascending).
  • barcode_id: Zero-based index of the transcript barcode in the codebook; forms a composite key with fov.
  • global_x: Transcript x coordinates (µm) in the experimental region; may be negative due to alignment.
  • global_y: Transcript y coordinates (µm) in the experimental region; may be negative due to alignment.
  • global_z: Zero‑based z‑position index.
  • x: The x-coordinate of the transcript (µm), within the coordinate space of the field of view.
  • y: The y-coordinate of the transcript (µm), within the coordinate space of the field of view.
  • fov: Zero-based field of view index; forms a composite key with barcode_id.
  • gene: Gene name associated with the transcript.

Data Access

The example data is hosted on Zenodo.

Follow the commands below to download the example data.

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work_dir=/path/to/work/directory
cd $work_dir
wget  https://zenodo.org/records/17953582/files/merscope_starter.raw.tar.gz
tar --strip-components=1 -zxvf merscope_starter.raw.tar.gz

Set Up the Environment

Pre-installed tools

Please ensure you have installed all required tools (See Installation).

Define paths to all required binaries and resources. Optionally, specify a fixed color map for consistent rendering.

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# ====
# Replace each placeholder with the actual path on your system.  
# ====

work_dir=/path/to/work/directory        # path to work directory that contains the downloaded input data
cd $work_dir

# Define paths to required binaries and resources
spatula=/path/to/spatula/binary         # path to spatula executable
punkst=/path/to/punkst/binary           # path to FICTURE2 (punkst) executable
tippecanoe=/path/to/tippecanoe/binary   # path to tippecanoe executable
pmtiles=/path/to/pmtiles/binary         # path to pmtiles executable
aws=/path/to/aws/cli/binary             # path to AWS CLI binary

# (Optional) Define path to color map. 
cmap=/path/to/color/map                 # Path to fixed color map. `CartLoader` includes one at cartloader/assets/fixed_color_map_256.tsv.

# Number of jobs
n_jobs=10                               # If not specified, the number of jobs defaults to 1.

# Activate the bioconda environment
conda activate ENV_NAME                 # replace ENV_NAME with your conda environment name

Define data ID and analysis parameters:

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# Unique identifier for your dataset
DATA_ID="merscope_hippo"                # change this to reflect your dataset name
PLATFORM="vizgen_merscope"              # platform information
SCALE=1                                 # scale from coordinate to micrometer

# LDA parameters
train_width=12                           # define LDA training hexagon width (comma-separated if multiple widths are applied)
n_factor=6,12                            # define number of factors in LDA training (comma-separated if multiple n-factor are applied)

How to Define Scaling Factors for MERSCOPE?

The MERSCOPE example data currently used here provides SGE in µm. Define scaling factor from coordinate to micrometer as 1.

SGE Format Conversion

Convert the raw input to the unified SGE format. See more details in its Reference page.

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cartloader sge_convert \
  --makefn sge_convert.mk \
  --platform ${PLATFORM} \
  --in-csv ./input.tsv.gz \
  --units-per-um ${SCALE} \
  --out-dir ./sge \
  --exclude-feature-regex '^(BLANK|Neg|Intergenic|Deprecated|Unassigned)' \
  --sge-visual \
  --spatula ${spatula} \
  --n-jobs ${n_jobs}
Parameter Required Type Description
--platform required string Platform (options: "10x_visium_hd", "seqscope", "10x_xenium", "bgi_stereoseq", "cosmx_smi", "vizgen_merscope", "pixel_seq", "generic")
--in-csv required string Path to the input TSV/CSV file
--units-per-um required float Scale to convert coordinates to microns (default: 1.0)
--out-dir required string Output directory for the converted SGE files
--makefn string File name for the generated Makefile (default: sge_convert.mk)
--exclude-feature-regex regex Pattern to exclude control features
--sge-visual flag Enable SGE visualization step (generates diagnostic image) (default: FALSE)
--spatula string Path to the spatula binary (default: spatula)
--n-jobs int Number of parallel jobs for processing (default: 1)

FICTURE Analysis

Compute spatial factors using punkst (FICTURE2 mode). See more details on the Reference page.

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cartloader run_ficture2 \
  --makefn run_ficture2.mk \
  --main \
  --in-transcript ./sge/transcripts.unsorted.tsv.gz \
  --in-feature ./sge/feature.clean.tsv.gz \
  --in-minmax ./sge/coordinate_minmax.tsv \
  --cmap-file ${cmap} \
  --exclude-feature-regex '^(mt-.*$|Gm\d+$)' \
  --out-dir ./ficture2 \
  --width ${train_width} \
  --n-factor ${n_factor} \
  --spatula ${spatula} \
  --ficture2 ${punkst} \
  --n-jobs ${n_jobs} \
  --threads ${n_jobs}
Parameter Required Type Description
--main required 1 flag Enable CartLoader to run all five steps
--in-transcript required string Path to input transcript-level SGE file
--out-dir required string Path to output directory
--width required int or comma-separated list LDA training hexagon width(s)
--n-factor required int or comma-separated list Number of LDA factors
--makefn string File name for the generated Makefile (default: run_ficture2.mk )
--in-feature string Path to input feature file
--in-minmax string Path to input coordinate min/max file
--cmap-file string Path to color map file
--exclude-feature-regex regex Pattern to exclude features
--spatula string Path to the spatula binary (default: spatula)
--ficture2 string Path to the punkst directory (defaults to punkst repository within submodules directory of CartLoader)
--n-jobs int Number of parallel jobs (default: 1)
--threads int Number of threads per job (default: 1)

1: CartLoader requires the user to specify at least one action. Available actions includes: --tile to run tiling step; --segment to run segmentation step; --init-lda to run LDA training step; --decode to run decoding step; --summary to run summarization step; --main to run all above five actions.

CartLoader Asset Packaging

Generate pmtiles and web-compatible tile directories. See more details in Reference page.

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# Example A: With FICTURE outputs (integrates factors + joins)
cartloader run_cartload2 \
  --makefn run_cartload2.mk \
  --fic-dir ./ficture2 \
  --out-dir ./cartload2 \
  --id ${DATA_ID} \
  --spatula ${spatula} \
  --pmtiles ${pmtiles} \
  --tippecanoe ${tippecanoe} \
  --n-jobs ${n_jobs} \
  --threads ${n_jobs}

# Example B: SGE-only (package molecules without FICTURE)
cartloader run_cartload2 \
  --makefn run_cartload2.mk \
  --sge-dir ./sge_convert \
  --out-dir ./cartload2 \
  --id ${DATA_ID} \
  --spatula ${spatula} \
  --pmtiles ${pmtiles} \
  --tippecanoe ${tippecanoe} \
  --n-jobs ${n_jobs} \
  --threads ${n_jobs}
Parameter Required Type Description
--out-dir required string Path to the output directory for PMTiles and web tiles
--id required string Dataset ID used for naming outputs and metadata
--fic-dir string Path to FICTURE outputs (enables factor layers + molecule–factor joins)
--sge-dir string Path to SGE outputs from sge_convert (enables SGE-only packaging)
--in-sge-assets string File name of SGE assets JSON/YAML in --sge-dir (default: sge_assets.json)
--in-fic-params string File name of FICTURE params JSON/YAML in --fic-dir (default: ficture.params.json)
--makefn string File name for the generated Makefile (default: run_cartload2.mk)
--spatula string Path to the spatula binary (default: spatula)
--pmtiles string Path to the pmtiles binary (default: pmtiles)
--tippecanoe string Path to the tippecanoe binary (default: tippecanoe)
--n-jobs int Number of parallel jobs (default: 1)
--threads int Number of threads per job (default: 4)

Upload to Data Repository

Choose a data repository to host/share your output

CartLoader supports two upload options (AWS and Zenodo) for storing PMTiles of SGE and spatial factors in a data repository.

Choose the one that best suits your needs.

AWS Uploads

Upload the generated CartLoader outputs to your designated AWS S3 directory:

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# AWS S3 target location for cartostore
S3_DIR=/s3/path/to/s3/dir              # Recommend to use DATA_ID as directory name, such as s3://bucket_name/xenium-v1-humanlung-cancer-ffpe

cartloader upload_aws \
  --in-dir ./cartload2 \
  --s3-dir "${S3_DIR}" \
  --aws ${aws} \
  --n-jobs ${n_jobs}
Parameter Required Type Description
--in-dir required string Path to the input directory containing the CartLoader asset packaging output
--s3-dir required string Path to the target S3 directory for uploading
--aws string Path to the AWS CLI binary
--n-jobs int Number of parallel jobs

Zenodo Uploads

Upload the generated CartLoader outputs to your designated Zenodo deposition or a new deposition.

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zenodo_token=/path/to/zenodo/token/file    # replace /path/to/zenodo/token/file by path to your zenodo token file

cartloader upload_zenodo \
  --in-dir ./cartload2 \
  --upload-method catalog \
  --zenodo-token $zenodo_token \
  --title  "Your Title" \
  --creators "Your Name" \
  --description "This is an example description"
Parameter Required Type Description
--in-dir required string Path to the input directory containing the CartLoader asset packaging output
--upload-method required string Method to determine which files to upload. Options: all to upload all files in --in-dir; catalog to upload files listed in a catalog YAML file; user_list to upload files explicitly listed via --in-list
--catalog-yaml string Required if --upload-method catalog. Path to catalog.yaml generated in run_cartload2. If absent, uses the catalog in the input directory specified by --in-dir.
--zenodo-token required string Path to your Zenodo access token file
--title required string Required when creating a new deposition (i.e., if --zenodo-deposition-id is omitted). Title for the new Zenodo deposition.
--creators required list of str List of creators in "Lastname, Firstname" format.

Output Data

See more details of output at the Reference pages for run_ficture2 and run_cartload2.