Data Submission/Data Upload - Revision history

MariaKim: /* Standardized and Controlled Vocabulary */

2026-05-07T22:18:27Z

Standardized and Controlled Vocabulary

← Older revision		Revision as of 22:18, 7 May 2026
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	=== best_biomarker_role ===		=== best_biomarker_role ===
	Report in all lowercase. Refer to the [https://www.ncbi.nlm.nih.gov/books/NBK326791/ BEST Resource] ~~for~~ the correct biomarker role.		Report in all lowercase. Refer to the [https://www.ncbi.nlm.nih.gov/books/NBK326791/ BEST Resource] to infer the correct biomarker role. Accepted role terms are:
			* diagnostic
			* monitoring
			* predictive
			* prognostic
			* response
			* risk
			* safety

	=== specimen ===		=== specimen ===

MariaKim at 22:14, 7 May 2026

2026-05-07T22:14:57Z

MariaKim at 22:52, 30 April 2026

2026-04-30T22:52:12Z

← Older revision		Revision as of 22:52, 30 April 2026
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	=== Condition ===		=== Condition ===
	Condition should be reported in all lowercase and ~~condition ID~~ (from Disease Ontology ID) should be provided in the following column		Condition should be reported in all lowercase and <code>condition_id</code> (from Disease Ontology, MONDO, or SNOMED) should be provided in the following column

	=== assessed_biomarker_entity ===		=== assessed_biomarker_entity ===
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	=== specimen ===		=== specimen ===
	Report in all lowercase and ~~specimen_ID~~ in the following column should be from UBERON.		Report in all lowercase and <code>specimen_id</code> in the following column should be from UBERON.

	=== biomarker ===		=== biomarker ===

MariaKim: /* Instructions to submit Biomarker Data */

2026-04-21T18:58:49Z

Instructions to submit Biomarker Data

← Older revision		Revision as of 18:58, 21 April 2026
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	# Other fields and annotations may also be collected from the data source, however if data is missing it can also be inferred or mapped from other sources.		# Other fields and annotations may also be collected from the data source, however if data is missing it can also be inferred or mapped from other sources.
	# Apply the following standards to the data when possible:		# Apply the following standards to the data when possible:
	## <code>condition_id</code> = DOID		## <code>condition_id</code> = <code>DOID:0080600</code>
	## <code>specimen_id</code> = UBERON		## <code>specimen_id</code> = <code>UBERON:0000178</code>
	## <code>evidence_source</code> = "SOURCE":"ID"		## <code>evidence_source</code> = <code>SOURCE:ID</code>, for example <code>PubMed:32677844</code>
	## For <code>assessed_biomarker_entity_id</code> please refer to this GitHub documentation for which standards to follow		## For <code>assessed_biomarker_entity_id</code> please refer to this GitHub documentation for which standards to follow
	# Provide extra annotations from your DCC/data with the agreed upon standards from the Biomarker Annotation RFC. This data does not have to follow the data model and can be submitted in a separate file.		# Provide extra annotations from your DCC/data with the agreed upon standards from the Biomarker Annotation RFC. This data does not have to follow the data model and can be submitted in a separate file.

MariaKim: /* Once data is formatted and cleaned please send any data to daniallmasood@gwu.edu */

2026-04-21T18:52:30Z

Once data is formatted and cleaned please send any data to daniallmasood@gwu.edu

← Older revision		Revision as of 18:52, 21 April 2026
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	# If curating data in tsv format: If biomarker rows are part of the same biomarker entry but differ on specimen, evidence, or role, then the biomarker_id for each row should be any string value that can uniquely identify which rows are part of the same biomarker.		# If curating data in tsv format: If biomarker rows are part of the same biomarker entry but differ on specimen, evidence, or role, then the biomarker_id for each row should be any string value that can uniquely identify which rows are part of the same biomarker.

	=== Once data is formatted and cleaned please send any data to ~~daniallmasood~~@gwu.edu ~~===~~		=== Submission ===
			Once data is formatted and cleaned please send any data to mazumder_lab@gwu.edu.
	# Concurrently with submitting data please fill out the BCO Information: Biomarker Data Google Form.		# Concurrently with submitting data please fill out the BCO Information: Biomarker Data Google Form.
	## This will give metadata and description on how biomarker data was collected and is important for adding submitted data to the Biomarker Data page. An example of a previous BCO is provided in the sheet and available on the biomarker data page as well. [https://hivelab.biochemistry.gwu.edu/biomarker-partnership/data/BCO_000435 Example]		## This will give metadata and description on how biomarker data was collected and is important for adding submitted data to the Biomarker Data page. An example of a previous BCO is provided in the sheet and available on the biomarker data page as well. [https://hivelab.biochemistry.gwu.edu/biomarker-partnership/data/BCO_000435 Example]

MariaKim at 18:51, 21 April 2026

2026-04-21T18:51:44Z

← Older revision		Revision as of 18:51, 21 April 2026
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	# Biomarker data collected should follow the biomarker data model.		# Biomarker data collected should follow the biomarker data model.
	# "Core" fields should be filled in from the data source where biomarker data is collected. Core fields:		# "Core" fields should be filled in from the data source where biomarker data is collected. Core fields:
	## biomarker		## <code>biomarker</code>
	## assessed_biomarker_entity and assessed_biomarker_entity_id		## <code>assessed_biomarker_entity</code> and <code>assessed_biomarker_entity_id</code>
	## condition and condition_id OR exposure_agent and exposure_agent_id		## <code>condition</code> and <code>condition_id</code> OR <code>exposure_agent</code> and <code>exposure_agent_id</code>
			## <code>component_group</code> containing integers (1, 2, 3...). A multicomponent biomarker must have the same integer in all rows related to that biomarker.
	# Other fields and annotations may also be collected from the data source, however if data is missing it can also be inferred or mapped from other sources.		# Other fields and annotations may also be collected from the data source, however if data is missing it can also be inferred or mapped from other sources.
	# Apply the following standards to the data when possible:		# Apply the following standards to the data when possible:
	## condition_id = DOID		## <code>condition_id</code> = DOID
	## specimen_id = UBERON		## <code>specimen_id</code> = UBERON
	## evidence_source = "SOURCE":"ID"		## <code>evidence_source</code> = "SOURCE":"ID"
	## For assessed_biomarker_entity_id please refer to this GitHub documentation for which standards to follow		## For <code>assessed_biomarker_entity_id</code> please refer to this GitHub documentation for which standards to follow
	# Provide extra annotations from your DCC/data with the agreed upon standards from the Biomarker Annotation RFC. This data does not have to follow the data model and can be submitted in a separate file.		# Provide extra annotations from your DCC/data with the agreed upon standards from the Biomarker Annotation RFC. This data does not have to follow the data model and can be submitted in a separate file.
	## For example: Relevant EHR data/LOINC data for biomarkers/biomarker entities can be included in a separate sheet.		## For example: Relevant EHR data/LOINC data for biomarkers/biomarker entities can be included in a separate sheet.
	# Create a tsv/json file with the agreed upon fields which correspond to the biomarker data model. The data dictionary provides details on what the different fields represent.		# Create a tsv/json file with the agreed upon fields which correspond to the biomarker data model. The data dictionary provides details on what the different fields represent.
	## The preferred method for data submission is a json file as it will help ingest the data into the existing data efficiently. However, tsv file submissions are ok as well. In the GitHub, data_conversion.py script exists in the Data Conversion Folder and it will handle tsv to json file conversion and json to tsv file conversion as well.		## The preferred method for data submission is a json file as it will help ingest the data into the existing data efficiently. However, tsv file submissions are ok as well. In the GitHub, <code>data_conversion.py</code> script exists in the Data Conversion Folder and it will handle tsv to json file conversion and json to tsv file conversion as well.
	## The biomarker data page has examples of tsv data submissions and how the data should be formatted with the appropriate biomarker fields. Example		## The biomarker data page has examples of tsv data submissions and how the data should be formatted with the appropriate biomarker fields. Example
	# For panel biomarkers, if the biomarkers are part of the same panel, the biomarker_id value for each biomarker should be any string value that can uniquely identify which rows are part of the same biomarker panel. Documentation		# For panel biomarkers, if the biomarkers are part of the same panel, the biomarker_id value for each biomarker should be any string value that can uniquely identify which rows are part of the same biomarker panel. Documentation

MariaKim: /* Protein Biomarker */

2025-10-22T16:24:10Z

Protein Biomarker

← Older revision		Revision as of 16:24, 22 October 2025
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	Should be reported as either:		Should be reported as either:

	* '''increased ~~protein~~ symbol level'''		* '''increased HGNC gene symbol level'''
	* '''decreased ~~protein~~ symbol level'''		* '''decreased HGNC gene symbol level'''
	* Example: increased IL6 level		* Example: increased IL6 level

MariaKim: /* Metabolite Biomarker */ fix casing

2025-10-21T15:19:38Z

Metabolite Biomarker: fix casing

← Older revision		Revision as of 15:19, 21 October 2025
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	* '''increased metabolite level'''		* '''increased metabolite level'''
	* '''decreased metabolite level'''		* '''decreased metabolite level'''
	* Example: increased ~~UREA~~ level		* Example: increased Urea level

	==== Protein Biomarker ====		==== Protein Biomarker ====

DaniallMasood: /* assessed_biomarker_entity */

2025-09-04T19:10:32Z

assessed_biomarker_entity

← Older revision		Revision as of 19:10, 4 September 2025
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	=== assessed_biomarker_entity ===		=== assessed_biomarker_entity ===
			assessed_biomarker_entity is the entity in which the change is assessed.

	Should start off with a capital letter but if it is just a gene then it should remain in all capitals (e.g Myosin-binding protein H-like or IL6).		Should start off with a capital letter but if it is just a gene then it should remain in all capitals (e.g Myosin-binding protein H-like or IL6).

DaniallMasood: /* assessed_biomarker_entity */

2025-06-25T19:28:52Z

assessed_biomarker_entity

← Older revision		Revision as of 19:28, 25 June 2025
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	=== assessed_biomarker_entity ===		=== assessed_biomarker_entity ===
	Should start off with a capital letter but if it is just a gene then it should remain in all capitals (e.g Myosin-binding protein H-like or IL6)		Should start off with a capital letter but if it is just a gene then it should remain in all capitals (e.g Myosin-binding protein H-like or IL6).

			If the entity type is anything but a gene the whole name should be typed out.

	=== assessed_entity_type ===		=== assessed_entity_type ===

← Older revision		Revision as of 22:14, 7 May 2026
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	## <code>component_group</code> containing integers (1, 2, 3...). A multicomponent biomarker must have the same integer in all rows related to that biomarker.		## <code>component_group</code> containing integers (1, 2, 3...). A multicomponent biomarker must have the same integer in all rows related to that biomarker.
	# Other fields and annotations may also be collected from the data source, however if data is missing it can also be inferred or mapped from other sources.		# Other fields and annotations may also be collected from the data source, however if data is missing it can also be inferred or mapped from other sources.
			## <code>evidence</code> is one or more exact citations from the evidence source (in most cases, it will be the PubMed publication).
	# Apply the following standards to the data when possible:		# Apply the following standards to the data when possible:
	## <code>condition_id</code> = <code>DOID:0080600</code>		## <code>condition_id</code> = <code>DOID:0080600</code>. Refer to https://disease-ontology.org/do/.
	## <code>specimen_id</code> = <code>UBERON:0000178</code>		## <code>specimen_id</code> = <code>UBERON:0000178</code>. Refer to https://www.ebi.ac.uk/ols4/ontologies/uberon.
			## <code>loinc_code</code> = <code>LOINC:100153-6</code>. Refer to https://loinc.org/ (you may need to create an account to access the search functionality).
	## <code>evidence_source</code> = <code>SOURCE:ID</code>, for example <code>PubMed:32677844</code>		## <code>evidence_source</code> = <code>SOURCE:ID</code>, for example <code>PubMed:32677844</code>
	## For <code>assessed_biomarker_entity_id</code> please refer to ~~this~~ GitHub documentation for which standards to follow		## For <code>assessed_biomarker_entity_id</code> please refer to the [https://github.com/clinical-biomarkers/biomarker-controlled-vocabulary GitHub documentation] for which standards to follow
	# Provide extra annotations from your DCC/data with the agreed upon standards from the Biomarker Annotation RFC. This data does not have to follow the data model and can be submitted in a separate file.		# Provide extra annotations from your DCC/data with the agreed upon standards from the Biomarker Annotation RFC. This data does not have to follow the data model and can be submitted in a separate file.
	## For example: Relevant EHR data/LOINC data for biomarkers/biomarker entities can be included in a separate sheet.		## For example: Relevant EHR data/LOINC data for biomarkers/biomarker entities can be included in a separate sheet.
	# Create a tsv/json file with the agreed upon fields which correspond to the biomarker data model. The data dictionary provides details on what the different fields represent.		# Create a tsv/json file with the agreed upon fields which correspond to the biomarker data model. The data dictionary provides details on what the different fields represent.
	## The preferred method for data submission is a json file as it will help ingest the data into the existing data efficiently. However, tsv file submissions are ok as well. In the GitHub, <code>data_conversion.py</code> script exists in the Data Conversion Folder and it will handle tsv to json file conversion and json to tsv file conversion as well.		## The preferred method for data submission is a json file as it will help ingest the data into the existing data efficiently. However, tsv file submissions are ok as well. In the GitHub, <code>data_conversion.py</code> script exists in the Data Conversion Folder and it will handle tsv to json file conversion and json to tsv file conversion as well.
	## The ~~biomarker~~ data page has examples of tsv data submissions and how the data should be formatted with the appropriate biomarker fields. Example		## The [BiomarkerKB data page] has examples of tsv data submissions and how the data should be formatted with the appropriate biomarker fields. Example
	# For panel biomarkers, if the biomarkers are part of the same panel, the biomarker_id value for each biomarker should be any string value that can uniquely identify which rows are part of the same biomarker panel. Documentation		# For panel biomarkers, if the biomarkers are part of the same panel, the biomarker_id value for each biomarker should be any string value that can uniquely identify which rows are part of the same biomarker panel. Documentation
	# If curating data in tsv format: If biomarker rows are part of the same biomarker entry but differ on specimen, evidence, or role, then the biomarker_id for each row should be any string value that can uniquely identify which rows are part of the same biomarker.		# If curating data in tsv format: If biomarker rows are part of the same biomarker entry but differ on specimen, evidence, or role, then the biomarker_id for each row should be any string value that can uniquely identify which rows are part of the same biomarker.
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	There is a standard way to report some biomarker data. This section covers how the actual biomarker should be reported and how other fields should be filled out.		There is a standard way to report some biomarker data. This section covers how the actual biomarker should be reported and how other fields should be filled out.

	=== ~~Condition~~ ===		=== condition ===
	~~Condition~~ should be reported in all lowercase and <code>condition_id</code> (from Disease Ontology, MONDO, or SNOMED) should be provided in the following column		<code>condition</code> should be reported in all lowercase and <code>condition_id</code> (from Disease Ontology, MONDO, or SNOMED) should be provided in the following column

	=== assessed_biomarker_entity ===		=== assessed_biomarker_entity ===