Update documentation to include assay models

README.md

@@ -36,7 +36,15 @@ This project contains the released versions of the JSON-LD schemas for the
 [Cancer Complexity Knowledge Portal] (CCKP), and more broadly, MC2 Center.
 You can learn more about the schemas/data models and other aspects of this
 project in our portal documentation - coming soon! The MC2 Center data model
-is in both CSV and JSON-LD format.
+is in both CSV and JSON-LD format, and individual entity schemas are also
+exported as standalone JSON Schemas in `./json_schemas`.
+
+Beyond the original entity types (Dataset, Study, Publication, Grant,
+Educational Resource, File, Tool, Person), the model also covers Biospecimen,
+Individual, and Model (non-human organism/cell line) entities, as well as
+assay-level metadata for imaging (multiplexed/single-channel imaging),
+NanoString GeoMx Digital Spatial Profiler (DSP) spatial transcriptomics,
+bulk/single-cell sequencing, and 10x Genomics Visium spatial transcriptomics.
 
 ## Folder Structure
 

all_valid_values.csv

@@ -7939,6 +7939,7 @@ treatmentType,Brachytherapy,
 treatmentType,Cellular Therapy,
 treatmentType,Chemotherapy,
 treatmentType,Concurrent Chemoradiation,
+treatmentType,Control,
 treatmentType,Conventional Radiotherapy,
 treatmentType,Electron Beam Radiation Therapy,
 treatmentType,External Beam Radiation Therapy,
@@ -10836,30 +10837,30 @@ rtPrimer,Poly-dT,
 rtPrimer,Feature barcoding,
 rtPrimer,Random,
 duo,Pending Annotation,
-duo,GRU,
-duo,PS,
-duo,GSO,
-duo,RTN,
-duo,CC,
-duo,NMDS,
-duo,NRES,
-duo,NPU,
-duo,DUM,
-duo,POA,
-duo,NCU,
-duo,NPUNCU,
-duo,NPOA,
-duo,IRB,
-duo,HMB,
-duo,PUB,
-duo,USE,
-duo,COL,
-duo,RST,
-duo,TSM,
-duo,MOR,
-duo,IST,
-duo,GSR,
-duo,DSR,
+duo,DUO:0000042,
+duo,DUO:0000027,
+duo,DUO:0000016,
+duo,DUO:0000029,
+duo,DUO:0000043,
+duo,DUO:0000015,
+duo,DUO:0000004,
+duo,DUO:0000045,
+duo,DUO:0000017,
+duo,DUO:0000011,
+duo,DUO:0000046,
+duo,DUO:0000018,
+duo,DUO:0000044,
+duo,DUO:0000021,
+duo,DUO:0000006,
+duo,DUO:0000019,
+duo,DUO:0000026,
+duo,DUO:0000020,
+duo,DUO:0000012,
+duo,DUO:0000025,
+duo,DUO:0000024,
+duo,DUO:0000028,
+duo,DUO:0000022,
+duo,DUO:0000007,
 duo,DUOPlus1,
 duo,DUOPlus2,
 duo,DUOPlus3,

docs/index.md

@@ -26,6 +26,12 @@ The platform supports the documentation and upload of a variety of resource type
 | **Files**                 | Individual research files to organize and reference within projects.                                    |
 | **Tools**                 | Software applications used for data analysis, visualization, and workflow automation.                   |
 | **Persons**               | Profiles of key individuals involved in research projects, including investigators and contributors.     |
+| **Biospecimens**          | Tissue, tumor, fluid, and other physical samples, including acquisition, preservation, and pathology details. |
+| **Individuals & Models**  | Human participants and the non-human organisms, cell lines, or organoids used as experimental models.  |
+| **Imaging**               | Multiplexed and single-channel imaging data, from raw images through channel, segmentation, and summary statistic levels. |
+| **NanoString GeoMx**      | Digital Spatial Profiler (DSP) spatial transcriptomics data, including ROI/segment annotations and processed expression levels. |
+| **Sequencing**            | Bulk and single-cell sequencing data, including RNA-specific library metadata and processed matrices.  |
+| **10x Visium**            | 10x Genomics Visium spatial transcriptomics data, from slide/capture-area metadata through processed levels. |
 
 By documenting your resources here, you make your work more discoverable, reproducible, and impactful.
 

docs/model/DataDSP.md

@@ -43,4 +43,4 @@ The table below includes sample values to demonstrate proper attribute usage.
 
 Below is the full field reference table with attributes and their descriptions.
 
-{{ read_csv('sharingPlans/reference.csv') }}
+{{ read_csv('sharingPlans/reference.csv', keep_default_na=False) }}

docs/model/biospecimen.md

@@ -0,0 +1,28 @@
+A **Biospecimen** entry documents a tissue, tumor, fluid, or other physical sample collected from an individual or a model organism/cell line for use in MC<sup>2</sup> Center-supported research. Biospecimen metadata captures how and when a specimen was acquired, its composition and preservation, and clinically relevant context such as disease type, tumor grade, morphology, and treatment history at the time of collection.
+
+This model outlines the key attributes needed to track a biospecimen from acquisition through processing, including its relationship to a parent individual, model, or another biospecimen (for derived specimens), as well as the pathology and preservation details that downstream assays depend on.
+
+
+## Why You Should Contribute Biospecimen Entries
+
+Contributing biospecimen entries ensures that every downstream dataset (imaging, sequencing, spatial transcriptomics, etc.) can be traced back to a well-documented physical sample. Complete biospecimen metadata makes it possible to reproduce experiments, correctly interpret assay results in their clinical context, and avoid ambiguity when the same specimen is used across multiple studies or assay types.
+
+
+### Who Should Be Contributing Biospecimen Entries?
+
+1. **Biobank and Specimen Coordinators** – Ensure specimens are consistently tracked from acquisition through distribution to assay cores.
+2. **Pathologists and Histology Staff** – Provide accurate morphology, tumor status, and preservation details that inform downstream analysis.
+3. **Research Staff and Lab Managers** – Maintain the link between specimens, the individuals/models they were derived from, and the assays performed on them.
+4. **Data Managers** – Ensure biospecimen records are complete before associated assay-level data (imaging, sequencing, etc.) is submitted.
+
+
+## Download Template
+
+You can download the [Biospecimen entry template](https://github.com/mc2-center/data-models/raw/main/templates/Biospecimen.csv), which includes all required fields, to streamline the data entry process.
+
+
+## Full Field Reference
+
+Below is the full field reference table with attributes and their descriptions.
+
+{{ read_csv('biospecimen/reference.csv', keep_default_na=False) }}

docs/model/dataset.md

@@ -47,4 +47,4 @@ The table below includes sample values to demonstrate proper attribute usage.
 
 Below is the full field reference table with attributes and their descriptions.
 
-{{ read_csv('dataset/reference.csv') }}
+{{ read_csv('dataset/reference.csv', keep_default_na=False) }}

docs/model/education.md

@@ -49,4 +49,4 @@ The table below includes sample values to demonstrate proper attribute usage.
 
 Below is the full field reference table with attributes and their descriptions.
 
-{{ read_csv('education/reference.csv') }}
+{{ read_csv('education/reference.csv', keep_default_na=False) }}

docs/model/file.md

@@ -49,4 +49,4 @@ The table below includes sample values to demonstrate proper attribute usage.
 
 Below is the full field reference table with attributes and their descriptions.
 
-{{ read_csv('file/reference.csv') }}
+{{ read_csv('file/reference.csv', keep_default_na=False) }}

docs/model/geomxAux.md

@@ -0,0 +1,28 @@
+A **NanoString GeoMx Auxiliary Files** entry documents the supporting, non-image and non-count files that accompany a NanoString GeoMx Digital Spatial Profiler (DSP) experiment. Rather than describing the imaging or expression data itself, this module tracks the auxiliary artifacts needed to fully interpret and reproduce a GeoMx run: the ROI/segment annotation file, the PKC probe kit configuration file, the lab worksheet(s) generated during the run, and the DSP `config.ini` file.
+
+These files are typically produced automatically by the GeoMx DSP instrument and software alongside the imaging and sequencing/count data, but they are easy to overlook when depositing a dataset. Capturing their Synapse identifiers here ensures that anyone reusing the imaging or expression data (Levels 1–3) can also locate the exact probe configuration, worksheet, and run settings that produced it.
+
+
+## Why You Should Contribute NanoString GeoMx Auxiliary Files Entries
+
+Contributing auxiliary file entries ensures that the configuration and worksheet files needed to interpret or reproduce a GeoMx DSP run are not lost or disconnected from the primary imaging and expression data, making the full experiment traceable and reusable by others.
+
+
+### Who Should Be Contributing NanoString GeoMx Auxiliary Files Entries?
+
+1. **Core Facility Staff** – Deposit the PKC, config, and worksheet files generated directly by the GeoMx DSP instrument.
+2. **Spatial Biology Researchers** – Ensure auxiliary files are linked to the correct experiment and biospecimens they support.
+3. **Computational Analysts** – Confirm that the probe kit and configuration files needed to reprocess or validate results are available and correctly referenced.
+4. **Data Managers** – Track auxiliary file completeness alongside the imaging and expression data deposited for a study.
+
+
+## Download Template
+
+You can download the [NanoStringGeoMxAuxiliaryFiles CSV template](https://github.com/mc2-center/data-models/raw/main/templates/NanoStringGeoMxAuxiliaryFiles.csv) to streamline data entry.
+
+
+## Full Field Reference
+
+Below is the full field reference table with attributes and their descriptions.
+
+{{ read_csv('geomxAux/reference.csv', keep_default_na=False) }}

docs/model/geomxImaging.md

@@ -0,0 +1,28 @@
+A **NanoString GeoMx Imaging** entry documents the images acquired directly by the GeoMx Digital Spatial Profiler (DSP) instrument during a spatial profiling run. This includes the standard file-level descriptors (format, species, design, assay) shared across the data model, along with GeoMx-specific attributes such as the imaging channel names captured and the Synapse ID(s) of tabular files containing the coordinate points for each Area of Illumination (AOI) found in the image.
+
+Because GeoMx images can vary widely in acquisition hardware and configuration, this module also captures detailed instrument- and file-format-level imaging metadata: platform model and manufacturer, acquisition software, objective and magnification, working distance, immersion type, field-of-view size and index, physical pixel size and dimension order, bit depth, plane count, and timepoint/z-stack structure. Imaging entries link forward to the sequencing outputs derived from the same run (Level 1 and Level 2) and to the ROI/segment annotations and biospecimen that were imaged, anchoring the full GeoMx data provenance chain.
+
+
+## Why You Should Contribute NanoString GeoMx Imaging Entries
+
+Contributing imaging entries ensures that the raw scan images underlying a GeoMx DSP experiment are properly cataloged with the acquisition and instrument details needed to interpret them, and are traceable to the ROIs, segments, and downstream expression data they informed.
+
+
+### Who Should Be Contributing NanoString GeoMx Imaging Entries?
+
+1. **Core Facility Staff** – Record the instrument, software, and acquisition settings used to capture GeoMx scan images.
+2. **Spatial Biology Researchers** – Confirm imaging metadata accurately reflects the tissue, channels, and regions profiled.
+3. **Computational Imaging Analysts** – Ensure channel names and AOI coordinate files are correctly linked so downstream expression data can be traced back to specific image regions.
+4. **Data Managers** – Track imaging files as they are deposited alongside sequencing and annotation data for a study.
+
+
+## Download Template
+
+You can download the [NanoStringGeoMxDSPImaging CSV template](https://github.com/mc2-center/data-models/raw/main/templates/NanoStringGeoMxDSPImaging.csv) to streamline data entry.
+
+
+## Full Field Reference
+
+Below is the full field reference table with attributes and their descriptions.
+
+{{ read_csv('geomxImaging/reference.csv', keep_default_na=False) }}

docs/model/geomxLevel1.md

@@ -0,0 +1,28 @@
+A **NanoString GeoMx Level 1** entry describes the raw sequencing files produced from a GeoMx Digital Spatial Profiler (DSP) experiment, prior to alignment or count conversion. This includes the assay type used in the DSP pipeline (RNA or Protein, run via nCounter or NGS) along with detailed next-generation sequencing (NGS) library metadata: library strategy, source material and molecule, selection method, layout, sequencing platform, read length, raw read counts, unique bases, sequencing coverage, and the library preparation kit name, vendor, and version.
+
+Level 1 entries represent the earliest and most complete record of what was sequenced during a GeoMx run, and they anchor the full data provenance chain — every downstream processed file (Level 2 count conversions and Level 3 processed counts) traces back to the raw reads documented here.
+
+
+## Why You Should Contribute NanoString GeoMx Level 1 Entries
+
+Contributing Level 1 entries ensures that raw GeoMx sequencing outputs are properly cataloged with the library preparation and sequencing details needed to interpret them, and are traceable back to the biospecimen and ROI/segment they were derived from.
+
+
+### Who Should Be Contributing NanoString GeoMx Level 1 Entries?
+
+1. **Core Facility Staff** – Document the library preparation kit, sequencing platform, and run parameters used to generate raw reads.
+2. **Spatial Biology Researchers** – Confirm that raw sequencing files are correctly linked to the biospecimen and segments profiled.
+3. **Computational Analysts** – Ensure sequencing metadata is complete so raw files can be correctly processed into Level 2 and Level 3 outputs.
+4. **Data Managers** – Track raw sequencing files as they are deposited to ensure completeness of the GeoMx data provenance chain.
+
+
+## Download Template
+
+You can download the [NanoStringGeoMxDSPLevel1 CSV template](https://github.com/mc2-center/data-models/raw/main/templates/NanoStringGeoMxDSPLevel1.csv) to streamline data entry.
+
+
+## Full Field Reference
+
+Below is the full field reference table with attributes and their descriptions.
+
+{{ read_csv('geomxLevel1/reference.csv', keep_default_na=False) }}

docs/model/geomxLevel2.md

@@ -0,0 +1,28 @@
+A **NanoString GeoMx Level 2** entry documents processed count conversion files (DCC/RCC) derived from a GeoMx Level 1 raw sequencing file. This level captures the same core library preparation and sequencing platform metadata as Level 1, along with the read-processing metrics generated during count conversion: stitched reads, aligned reads, deduplicated reads, trimmed reads, percent reads mapping at Q30 (MapQ30), unique bases, sequencing coverage, the genomic reference used, and the software and version that performed the conversion.
+
+Level 2 entries represent the intermediate step between raw sequencing reads and analysis-ready processed counts, preserving a clear lineage back to the Level 1 raw reads that produced them while capturing the alignment and deduplication metrics needed to assess data quality.
+
+
+## Why You Should Contribute NanoString GeoMx Level 2 Entries
+
+Contributing Level 2 entries ensures that the read-processing and alignment steps between raw reads and final count data are documented with enough detail for others to assess data quality and trace processed counts back to their source reads.
+
+
+### Who Should Be Contributing NanoString GeoMx Level 2 Entries?
+
+1. **Computational Analysts** – Document the software, genomic reference, and alignment/deduplication metrics used to generate count conversion files.
+2. **Core Facility Staff** – Provide the sequencing platform and library details carried through from Level 1.
+3. **Bioinformatics Pipeline Developers** – Record workflow and software versions to support reproducibility of the count conversion step.
+4. **Data Managers** – Maintain consistent, portal-ready metadata linking Level 1 raw reads to Level 2 processed outputs.
+
+
+## Download Template
+
+You can download the [NanoStringGeoMxDSPLevel2 CSV template](https://github.com/mc2-center/data-models/raw/main/templates/NanoStringGeoMxDSPLevel2.csv) to streamline data entry.
+
+
+## Full Field Reference
+
+Below is the full field reference table with attributes and their descriptions.
+
+{{ read_csv('geomxLevel2/reference.csv', keep_default_na=False) }}

docs/model/geomxLevel3.md

@@ -0,0 +1,28 @@
+A **NanoString GeoMx Level 3** entry documents the fully processed count data produced by the NanoString GeoMx DSP pipeline, such as final probe- or target-level expression matrices. This level captures the unique probe and unique target counts represented in the file, the matrix type (e.g. raw, normalized, or background-subtracted counts), and the software, workflow, and parameters used to generate the processed output, including a link to the workflow for reproducibility.
+
+Level 3 entries represent the analysis-ready data products most commonly used for downstream statistical analysis, while still preserving a clear lineage back to the Level 2 count conversion and Level 1 raw reads that produced them.
+
+
+## Why You Should Contribute NanoString GeoMx Level 3 Entries
+
+Contributing Level 3 entries ensures that processed count data is documented with enough workflow and provenance detail for others to understand exactly how it was derived, and to confidently reuse it in downstream analyses shared through the CCKP.
+
+
+### Who Should Be Contributing NanoString GeoMx Level 3 Entries?
+
+1. **Computational Analysts** – Document the workflow, parameters, and matrix type used to generate processed count data.
+2. **Bioinformatics Pipeline Developers** – Record the software and workflow versions that produced the processed outputs, supporting reproducibility.
+3. **Spatial Biology Researchers** – Track which processed data products correspond to which raw reads and ROI/segments.
+4. **Data Managers** – Maintain consistent, portal-ready metadata for processed GeoMx outputs shared through the CCKP.
+
+
+## Download Template
+
+You can download the [NanoStringGeoMxDSPLevel3 CSV template](https://github.com/mc2-center/data-models/raw/main/templates/NanoStringGeoMxDSPLevel3.csv) to streamline data entry.
+
+
+## Full Field Reference
+
+Below is the full field reference table with attributes and their descriptions.
+
+{{ read_csv('geomxLevel3/reference.csv', keep_default_na=False) }}