02. Data Dictionary • coMMpass

Overview

See the Glossary for term definitions and units reference used throughout this project.

Describes all variables in the MMRF CoMMpass dataset from the GDC
CoMMpass: longitudinal observational study of ~1,000 newly diagnosed multiple myeloma patients
Variables span clinical demographics, biospecimen metadata, and RNA-seq gene expression

Data sources:

Complete Data Dictionary

Searchable table of all variables available in the CoMMpass dataset with types, categories, and descriptions.

CoMMpass Data Dictionary (38 variables). Click column headers to sort; use filters to search. GDC links open the official GDC data dictionary page. Source: GDC clinical + biospecimen + RNA-seq metadata. See glossary for term definitions and units-table for measurement conventions.
	variable	category	data_type	units	description	typical_range	gdc_link
1	submitter_id	clinical	character	NA	Patient identifier assigned by the submitting institution (MMRF)	MMRF_0001 to MMRF_2149	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=clinical” target=“_blank”>GDC</a>
2	project_id	clinical	character	NA	GDC project identifier	MMRF-COMMPASS	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=clinical” target=“_blank”>GDC</a>
3	age_at_diagnosis	clinical	integer	days	Age at primary diagnosis in DAYS (divide by 365.25 for years). GDC stores all ages in days.	10000-35000 (approx 27-96 years)	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=clinical” target=“_blank”>GDC</a>
4	gender	clinical	character	NA	Patient sex/gender	female, male, not reported	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=clinical” target=“_blank”>GDC</a>
5	race	clinical	character	NA	Patient race category per NIH guidelines	white, black or african american, asian, not reported, other	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=clinical” target=“_blank”>GDC</a>
6	ethnicity	clinical	character	NA	Patient ethnicity per NIH guidelines	not hispanic or latino, hispanic or latino, not reported	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=clinical” target=“_blank”>GDC</a>
7	vital_status	clinical	character	NA	Patient vital status at last follow-up	Alive, Dead, Not Reported	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=clinical” target=“_blank”>GDC</a>
8	days_to_death	clinical	integer	days	Number of days from diagnosis to death. NA if patient is alive.	0-5000+	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=clinical” target=“_blank”>GDC</a>
9	days_to_last_follow_up	clinical	integer	days	Number of days from diagnosis to last follow-up. NA if patient is deceased.	0-5000+	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=clinical” target=“_blank”>GDC</a>
10	primary_diagnosis	clinical	character	NA	ICD-O-3 morphology code description for the primary diagnosis	Plasma cell myeloma, Myeloma NOS	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=clinical” target=“_blank”>GDC</a>
11	disease_type	clinical	character	NA	Type of disease studied	Multiple Myeloma	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=clinical” target=“_blank”>GDC</a>
12	site_of_resection_or_biopsy	clinical	character	NA	Anatomic site of tissue sample collection	Bone marrow, Blood	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=clinical” target=“_blank”>GDC</a>
13	tissue_or_organ_of_origin	clinical	character	NA	Anatomic site of the disease origin	Bone marrow	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=clinical” target=“_blank”>GDC</a>
14	year_of_diagnosis	clinical	integer	year	Calendar year of primary diagnosis	2005-2020	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=clinical” target=“_blank”>GDC</a>
15	classification_of_tumor	clinical	character	NA	Tumor classification	primary, recurrence, metastasis, not reported	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=clinical” target=“_blank”>GDC</a>
16	prior_malignancy	clinical	character	NA	Whether patient had a prior malignancy	yes, no, not reported	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=clinical” target=“_blank”>GDC</a>
17	prior_treatment	clinical	character	NA	Whether patient received prior treatment	yes, no, not reported	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=clinical” target=“_blank”>GDC</a>
18	ajcc_staging_system_edition	clinical	character	NA	AJCC staging edition used	various editions	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=clinical” target=“_blank”>GDC</a>
19	days_to_last_known_disease_status	clinical	integer	days	Days from diagnosis to last disease status assessment	0-5000+	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=clinical” target=“_blank”>GDC</a>
20	sample_submitter_id	biospecimen	character	NA	Sample identifier assigned by submitting institution	MMRF_0001_1_BM, etc.	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=sample” target=“_blank”>GDC</a>
21	sample_id	biospecimen	character	NA	GDC-assigned UUID for the sample	UUID format	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=sample” target=“_blank”>GDC</a>
22	sample_type	biospecimen	character	NA	Type of sample collected	Primary Blood Derived Cancer - Bone Marrow, etc.	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=sample” target=“_blank”>GDC</a>
23	sample_type_id	biospecimen	character	NA	Numeric code for sample type	01, 09, 10, etc.	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=sample” target=“_blank”>GDC</a>
24	tissue_type	biospecimen	character	NA	Whether tissue is tumor or normal	Tumor, Normal	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=sample” target=“_blank”>GDC</a>
25	preservation_method	biospecimen	character	NA	Method used to preserve the sample	FFPE, Frozen, etc.	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=sample” target=“_blank”>GDC</a>
26	composition	biospecimen	character	NA	Sample composition category	Bone Marrow Components, Blood Derived	<a href=“https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=sample” target=“_blank”>GDC</a>
27	gene_id	rnaseq_counts	character	NA	Ensembl gene identifier (ENSG with version)	ENSG00000000003.15	<a href=“https://docs.gdc.cancer.gov/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline/” target=“_blank”>GDC</a>
28	unstranded	rnaseq_counts	integer	raw counts	Unstranded read counts from STAR aligner. Use for DESeq2/edgeR analysis.	0-1000000+	<a href=“https://docs.gdc.cancer.gov/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline/” target=“_blank”>GDC</a>
29	stranded_first	rnaseq_counts	integer	raw counts	First-strand read counts (dUTP protocol)	0-1000000+	<a href=“https://docs.gdc.cancer.gov/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline/” target=“_blank”>GDC</a>
30	stranded_second	rnaseq_counts	integer	raw counts	Second-strand read counts	0-1000000+	<a href=“https://docs.gdc.cancer.gov/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline/” target=“_blank”>GDC</a>
31	tpm_unstranded	rnaseq_counts	numeric	TPM	Transcripts Per Million (unstranded). Normalized for gene length and sequencing depth.	0-100000+	<a href=“https://docs.gdc.cancer.gov/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline/” target=“_blank”>GDC</a>
32	fpkm_unstranded	rnaseq_counts	numeric	FPKM	Fragments Per Kilobase of transcript per Million mapped reads (unstranded).	0-100000+	<a href=“https://docs.gdc.cancer.gov/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline/” target=“_blank”>GDC</a>
33	fpkm_uq_unstranded	rnaseq_counts	numeric	FPKM-UQ	Upper quartile normalized FPKM (unstranded).	0-100000+	<a href=“https://docs.gdc.cancer.gov/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline/” target=“_blank”>GDC</a>
34	gene_name	rnaseq_metadata	character	NA	HGNC gene symbol	TP53, KRAS, MYC, etc.	<a href=“https://docs.gdc.cancer.gov/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline/” target=“_blank”>GDC</a>
35	gene_type	rnaseq_metadata	character	NA	Biotype from GENCODE annotation	protein_coding, lncRNA, miRNA, processed_pseudogene, etc.	<a href=“https://docs.gdc.cancer.gov/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline/” target=“_blank”>GDC</a>
36	barcode	rnaseq_metadata	character	NA	TCGA-style barcode for the sample	MMRF-COMMPASS-XXXX-TBM-…	<a href=“https://docs.gdc.cancer.gov/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline/” target=“_blank”>GDC</a>
37	patient	rnaseq_metadata	character	NA	Patient identifier extracted from barcode	MMRF-COMMPASS-XXXX	<a href=“https://docs.gdc.cancer.gov/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline/” target=“_blank”>GDC</a>
38	sample_type	rnaseq_metadata	character	NA	Sample type from barcode decoding	Primary Blood Derived Cancer - Bone Marrow	<a href=“https://docs.gdc.cancer.gov/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline/” target=“_blank”>GDC</a>

Clinical Data

Patient demographics, disease characteristics, and outcomes
Downloaded via TCGAbiolinks::GDCquery_clinic()
All time/age variables in days (see units reference)

Sample Rows

First 5 rows of key clinical variables. submitter_id = MMRF patient ID; age_at_diagnosis = days; iss_stage = International Staging System (I/II/III). Full dataset: 995 patients x 88 variables.
submitter_id	age_at_diagnosis	gender	race	vital_status	days_to_death	days_to_last_follow_up	iss_stage
MMRF_2240	24502	male	white	Alive	NA	832	III
MMRF_1038	25255	male	white	Dead	1753	1753	III
MMRF_1054	21310	female	white	Alive	NA	1828	II
MMRF_2174	31241	male	white	Dead	425	425	Unknown
MMRF_2168	18590	male	black or african american	Alive	NA	877	I

Summary

Total patients: 995
Variables: 88
Data completeness: 95.8%

Column Structure

Structure of all 88 clinical variables for 995 patients. Time variables are in DAYS (GDC convention). Columns reordered: IDs > demographics > time > vital status > disease > other. See glossary for units reference.
	Column	Type	Non_NA	Pct_Complete	N_Unique	Example
1	project	character	995	100%	1	MMRF-COMMPASS
2	submitter_id	character	995	100%	995	MMRF_1016, MMRF_1020, MMRF_1021
3	submitter_id	character	995	100%	995	MMRF_1016, MMRF_1020, MMRF_1021
4	submitter_sample_ids	character	995	100%	995	MMRF_1016_1_BM_CD138pos,MMRF_1016_1_PB_WBC, MMRF_1020_3_BM_CD138pos,MMRF_1020_3_PB_Whole, MMRF_1021_1_BM_CD138pos,MMRF_1021_2_PB_CD3pos
5	submitter_id	character	995	100%	995	MMRF_10161, MMRF_10201, MMRF_10211
6	age_at_diagnosis_days	character	995	100%	927	NA, 17034, 18560
7	race	character	995	100%	6	white, not reported, black or african american
8	gender	character	995	100%	2	male, female
9	ethnicity	character	995	100%	3	not hispanic or latino, not reported, hispanic or latino
10	age_at_index_days	integer	995	100%	59	min=27 med=63 max=89
11	days_to_last_known_disease_status_days	character	995	100%	693	1, 997, 617
12	days_to_best_overall_response	character	995	100%	1	NA
13	days_to_diagnosis	character	995	100%	1	NA
14	days_to_last_follow_up_days	character	995	100%	693	1, 997, 617
15	year_of_diagnosis	character	995	100%	1	NA
16	days_to_recurrence	character	995	100%	1	NA
17	days_to_birth	integer	953	96%	926	min=-32800 med=-23200 max=-10100
18	year_of_birth	logical	0	0%	0	(all NA)
19	days_to_death_days	integer	191	19%	176	min=8 med=475 max=1750
20	year_of_death	logical	0	0%	0	(all NA)
21	last_known_disease_status	character	995	100%	1	Unknown tumor status
22	cause_of_death	character	188	19%	2	Cancer Related, Not Cancer Related
23	vital_status	character	995	100%	2	Alive, Dead
24	primary_site	character	995	100%	1	Hematopoietic and reticuloendothelial systems
25	irs_stage	character	995	100%	1	NA
26	iss_stage	character	995	100%	4	II, I, III
27	ajcc_pathologic_stage	character	995	100%	1	NA
28	ann_arbor_clinical_stage	character	995	100%	1	NA
29	enneking_msts_stage	character	995	100%	1	NA
30	inrg_stage	character	995	100%	1	NA
31	tissue_or_organ_of_origin	character	995	100%	1	Bone marrow
32	cog_liver_stage	character	995	100%	1	NA
33	inpc_grade	character	995	100%	1	NA
34	wilms_tumor_histologic_subtype	character	995	100%	1	NA
35	classification_of_tumor	character	995	100%	1	NA
36	cog_renal_stage	character	995	100%	1	NA
37	figo_stage	character	995	100%	1	NA
38	inss_stage	character	995	100%	1	NA
39	tumor_confined_to_organ_of_origin	character	995	100%	1	NA
40	primary_diagnosis	character	995	100%	1	Multiple myeloma
41	ajcc_clinical_stage	character	995	100%	1	NA
42	metastasis_at_diagnosis	character	995	100%	1	NA
43	enneking_msts_tumor_site	character	995	100%	1	NA
44	ann_arbor_pathologic_stage	character	995	100%	1	NA
45	method_of_diagnosis	character	995	100%	1	NA
46	diagnosis_id	character	995	100%	995	0073d350-15ca-4e89-9326-d95543cf778c, 00a8b803-c44b-41ba-9d44-79c1b87a74aa, 00fe922e-5ecb-4936-a91d-6680d3f393c6
47	site_of_resection_or_biopsy	character	995	100%	1	Bone marrow
48	first_symptom_prior_to_diagnosis	character	995	100%	1	NA
49	tumor_grade	character	995	100%	1	Unknown
50	enneking_msts_grade	character	995	100%	1	NA
51	disease_type	character	995	100%	1	Plasma Cell Tumors
52	created_datetime	character	995	100%	1	2018-07-10T14:08:13.021252-05:00
53	enneking_msts_metastasis	character	995	100%	1	NA
54	esophageal_columnar_dysplasia_degree	character	995	100%	1	NA
55	child_pugh_classification	character	995	100%	1	NA
56	state	character	995	100%	1	released
57	prior_treatment	character	995	100%	1	NA
58	cog_rhabdomyosarcoma_risk_group	character	995	100%	1	NA
59	ajcc_pathologic_t	character	995	100%	1	NA
60	morphology	character	995	100%	1	9732/3
61	ajcc_pathologic_n	character	995	100%	1	NA
62	ajcc_pathologic_m	character	995	100%	1	NA
63	irs_group	character	995	100%	1	NA
64	medulloblastoma_molecular_classification	character	995	100%	1	NA
65	residual_disease	character	995	100%	1	NA
66	ann_arbor_b_symptoms	character	995	100%	1	NA
67	icd_10_code	character	995	100%	1	NA
68	synchronous_malignancy	character	995	100%	1	NA
69	burkitt_lymphoma_clinical_variant	character	995	100%	1	NA
70	supratentorial_localization	character	995	100%	1	NA
71	ishak_fibrosis_score	character	995	100%	1	NA
72	goblet_cells_columnar_mucosa_present	character	995	100%	1	NA
73	laterality	character	995	100%	1	NA
74	cog_neuroblastoma_risk_group	character	995	100%	1	NA
75	updated_datetime	character	995	100%	2	2019-06-24T08:07:19.797044-05:00, 2019-08-21T12:47:37.999949-05:00
76	prior_malignancy	character	995	100%	1	NA
77	best_overall_response	character	995	100%	1	NA
78	ann_arbor_extranodal_involvement	character	995	100%	1	NA
79	mitosis_karyorrhexis_index	character	995	100%	1	NA
80	ajcc_staging_system_edition	character	995	100%	1	NA
81	esophageal_columnar_metaplasia_present	character	995	100%	1	NA
82	ajcc_clinical_m	character	995	100%	1	NA
83	ajcc_clinical_n	character	995	100%	1	NA
84	ajcc_clinical_t	character	995	100%	1	NA
85	inpc_histologic_group	character	995	100%	1	NA
86	gastric_esophageal_junction_involvement	character	995	100%	1	NA
87	progression_or_recurrence	character	995	100%	1	unknown
88	demographic_id	character	995	100%	995	0059d727-d660-43b7-bfc5-e8e374f813bf, 00aa6c25-74bf-4a10-b015-3873314906b5, 00af936c-0b23-4c49-94ac-254f89600cf0

Biospecimen Data

Tissue samples collected from patients
Includes sample type, tissue type, and preservation method
Total records: 2,119
Variables: 31

Biospecimen data columns for 2119 records (31 variables). Column = field name from GDC biospecimen endpoint; R Type = data type in R; Non-NA = non-missing count; % Complete = data completeness; Unique Values = cardinality. Source: GDC biospecimen API. See clinical table for patient-level demographics and exploratory-analysis for sample-type distribution.
	Column	Type	Non_NA	Pct_Complete	N_Unique
distributor_reference	distributor_reference	logical	0	0%	0
tumor_descriptor	tumor_descriptor	character	2119	100%	3
sample_id	sample_id	character	2119	100%	2119
diagnosis_pathologically_confirmed	diagnosis_pathologically_confirmed	logical	0	0%	0
sample_type	sample_type	character	2119	100%	5
created_datetime	created_datetime	character	2119	100%	1
distance_normal_to_tumor	distance_normal_to_tumor	logical	0	0%	0
time_between_excision_and_freezing	time_between_excision_and_freezing	logical	0	0%	0
growth_rate	growth_rate	logical	0	0%	0
updated_datetime	updated_datetime	character	2119	100%	1
days_to_collection	days_to_collection	logical	0	0%	0
method_of_sample_procurement	method_of_sample_procurement	logical	0	0%	0
state	state	character	2119	100%	1
initial_weight	initial_weight	logical	0	0%	0
preservation_method	preservation_method	character	2119	100%	1
intermediate_dimension	intermediate_dimension	logical	0	0%	0
passage_count	passage_count	logical	0	0%	0
time_between_clamping_and_freezing	time_between_clamping_and_freezing	logical	0	0%	0
freezing_method	freezing_method	logical	0	0%	0
pathology_report_uuid	pathology_report_uuid	logical	0	0%	0
submitter_id	submitter_id	character	2119	100%	2119
tumor_code_id	tumor_code_id	logical	0	0%	0
shortest_dimension	shortest_dimension	logical	0	0%	0
biospecimen_anatomic_site	biospecimen_anatomic_site	logical	0	0%	0
specimen_type	specimen_type	character	2119	100%	2
biospecimen_laterality	biospecimen_laterality	logical	0	0%	0
days_to_sample_procurement	days_to_sample_procurement	integer	2119	100%	223
longest_dimension	longest_dimension	logical	0	0%	0
current_weight	current_weight	logical	0	0%	0
catalog_reference	catalog_reference	logical	0	0%	0
tissue_type	tissue_type	character	2119	100%	2

RNA-seq Data

RNA-seq gene expression generated using the STAR aligner
Quantified against GENCODE annotations
Available in multiple quantification types (raw counts, TPM, FPKM)
See units reference for quantification units

Dimensions

Samples: 100
Genes: 60,660
Assays: unstranded, stranded_first, stranded_second, tpm_unstrand, fpkm_unstrand, fpkm_uq_unstrand

Gene biotypes from GENCODE annotations. 60,660 total gene entries. protein_coding genes are the primary analysis target.
	Biotype	Count	Percentage
1	protein_coding	19962	32.9%
2	lncRNA	16901	27.9%
3	processed_pseudogene	10167	16.8%
4	unprocessed_pseudogene	2614	4.3%
5	misc_RNA	2212	3.6%
6	snRNA	1901	3.1%
7	miRNA	1881	3.1%
8	TEC	1057	1.7%
9	snoRNA	943	1.6%
10	transcribed_unprocessed_pseudogene	939	1.5%
11	transcribed_processed_pseudogene	500	0.8%
12	rRNA_pseudogene	497	0.8%
13	IG_V_pseudogene	187	0.3%
14	IG_V_gene	145	0.2%
15	transcribed_unitary_pseudogene	138	0.2%
16	TR_V_gene	106	0.2%
17	unitary_pseudogene	98	0.2%
18	TR_J_gene	79	0.1%
19	scaRNA	49	0.1%
20	polymorphic_pseudogene	48	0.1%
21	rRNA	47	0.1%
22	IG_D_gene	37	0.1%
23	TR_V_pseudogene	33	0.1%
24	Mt_tRNA	22	0.0%
25	IG_J_gene	18	0.0%
26	pseudogene	18	0.0%
27	IG_C_gene	14	0.0%
28	IG_C_pseudogene	9	0.0%
29	ribozyme	8	0.0%
30	TR_C_gene	6	0.0%
31	sRNA	5	0.0%
32	TR_D_gene	4	0.0%
33	TR_J_pseudogene	4	0.0%
34	IG_J_pseudogene	3	0.0%
35	Mt_rRNA	2	0.0%
36	translated_processed_pseudogene	2	0.0%
37	IG_pseudogene	1	0.0%
38	scRNA	1	0.0%
39	translated_unprocessed_pseudogene	1	0.0%
40	vault_RNA	1	0.0%

RNA-seq sample metadata columns from the SummarizedExperiment colData (42 columns, 100 samples). Column = metadata field name; Type = R class; N_Unique = number of distinct values. Source: GDC mRNA-seq pipeline via TCGAbiolinks. See data-dictionary clinical table for patient-level variables.
	Column	Type	N_Unique
barcode	barcode	character	100
sample	sample	character	100
patient	patient	character	98
sample_submitter_id	sample_submitter_id	character	100
tumor_descriptor	tumor_descriptor	character	2
sample_id	sample_id	character	100
sample_type	sample_type	character	3
state	state	character	1
preservation_method	preservation_method	character	1
submitter_id	submitter_id	character	98
specimen_type	specimen_type	character	2
days_to_sample_procurement	days_to_sample_procurement	integer	47
tissue_type	tissue_type	character	1
iss_stage	iss_stage	character	4
treatments	treatments	list	98
tissue_or_organ_of_origin	tissue_or_organ_of_origin	character	1
age_at_diagnosis	age_at_diagnosis	integer	92
days_to_last_known_disease_status	days_to_last_known_disease_status	numeric	93
morphology	morphology	character	1
last_known_disease_status	last_known_disease_status	character	1
primary_diagnosis	primary_diagnosis	character	1
diagnosis_id	diagnosis_id	character	98
site_of_resection_or_biopsy	site_of_resection_or_biopsy	character	1
tumor_grade	tumor_grade	character	1
progression_or_recurrence	progression_or_recurrence	character	1
cause_of_death	cause_of_death	character	2
race	race	character	5
gender	gender	character	2
ethnicity	ethnicity	character	3
vital_status	vital_status	character	2
age_at_index	age_at_index	integer	38
days_to_birth	days_to_birth	integer	92
demographic_id	demographic_id	character	98
days_to_death	days_to_death	integer	27
bcr_patient_barcode	bcr_patient_barcode	character	100
primary_site	primary_site	list	1
dbgap_accession_number	dbgap_accession_number	character	1
project_id	project_id	character	1
disease_type	disease_type	list	1
name	name	character	1
releasable	releasable	logical	1
released	released	logical	1

Treatment Data

Treatment records extracted from GDC API (7,184 records, 994 patients)
Each row = one drug administration for one patient
Includes therapeutic agent, line of therapy, and timing

Sample Rows

First 5 treatment records from GDC API. Each row = one drug administration for one patient. regimen_or_line_of_therapy = treatment line (First, Second, etc). Full dataset: 7184 records, 994 patients.
public_id	therapeutic_agents	regimen_or_line_of_therapy	days_to_treatment_start	days_to_treatment_end
MMRF_2240	Dexamethasone	Second line of therapy	849	NA
MMRF_2240	Melphalan	First line of therapy	733	733
MMRF_2240	Dexamethasone	First line of therapy	1	91
MMRF_2240	Cyclophosphamide	First line of therapy	1	68
MMRF_2240	Lenalidomide	First line of therapy	91	202

Column Name Mappings

GDC uses standardized column names. Common aliases used in analysis:

GDC column name mappings to common aliases used in analysis code (7 mappings). GDC_Column = official GDC field name; Common_Alias = shorthand used in pipeline code. Key: age_at_diagnosis is in DAYS (not years); vital_status determines whether days_to_death or days_to_last_follow_up is used for OS time. See data-dictionary for full variable definitions.
	GDC_Column	Common_Alias	Notes
1	submitter_id	patient_id	Unique patient identifier
2	age_at_diagnosis	age_days	In days, not years (divide by 365.25)
3	vital_status	status	Alive/Dead
4	days_to_death	os_time (if dead)	Overall survival time
5	days_to_last_follow_up	os_time (if alive)	Censoring time
6	gender	sex	male/female
7	primary_diagnosis	diagnosis	ICD-O-3 morphology

Units Reference

For the complete units reference table (age/time in days, expression quantification types), see the Glossary units reference.

Key rule: All age and time variables are stored in DAYS by GDC. This is the single most common source of errors in GDC analyses.

Data Sources & Links

GDC Portal: https://portal.gdc.cancer.gov/projects/MMRF-COMMPASS
GDC Data Dictionary: https://docs.gdc.cancer.gov/Data_Dictionary/viewer/
GDC mRNA Analysis Pipeline: https://docs.gdc.cancer.gov/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline/
MMRF CoMMpass Study: https://themmrf.org/research/commpass-study/
GENCODE: https://www.gencodegenes.org/
Ensembl: https://www.ensembl.org/

For exploratory analysis using these variables, see the EDA vignette.

R Code Examples

Loading Data

How to load CoMMpass data from parquet files and query with DuckDB.

Show code

safe_tar_read("code_dd_load_data")

library(coMMpass)

Load clinical data from parquet

clinical <- query_commpass_parquet(“clinical”)

Load with DuckDB lazy evaluation

con <- DBI::dbConnect(duckdb::duckdb()) clinical_tbl <- get_commpass_tbl(“clinical”, con = con) result <- clinical_tbl |> dplyr::filter(gender == “female”) |> dplyr::select(submitter_id, age_at_diagnosis, vital_status) |> dplyr::mutate(age_years = age_at_diagnosis / 365.25) |> dplyr::collect() DBI::dbDisconnect(con, shutdown = TRUE)

Exploring the Dictionary

Programmatic access to variable documentation and metadata.

Show code

safe_tar_read("code_dd_explore_dict")

dd <- get_commpass_data_dictionary()

Find all clinical variables

dplyr::filter(dd, category == “clinical”)

Get detailed docs for a variable

docs <- get_variable_docs(“age_at_diagnosis”) cat(docs$usage_notes)

Data Sources

Results in this vignette are derived from the MMRF CoMMpass study (MMRF-COMMPASS, ~1,143 patients), downloaded via TCGAbiolinks. The pipeline runs with a configurable sample_limit (default 200; CI uses 20).

For full citations, data access tiers, and the distinction between pipeline data and synthetic test data, see the Data Sources vignette.

Recent Changes

Recent project commits with lines added, files changed, and change categories.

Last 20 project commits with change statistics. Date = commit date; Type = conventional-commit prefix (feat/fix/docs/ci/refactor/test/chore). Files = number of files modified; +Lines/-Lines = lines added/removed. Source: git log –numstat. See changes-by-type table for aggregate breakdown.
date	type	summary	n_files	lines_added	lines_removed	file_categories
2026-03-14	Bug Fix	fix(pipeline): Fix 11 NULL targets — DE condition, ID matching, consensus type	41	146	47	Other, R Source
2026-03-14	Bug Fix	fix(cachix): Remove –watch-mode auto flag (already default)	1	1	1	Other
2026-03-14	Bug Fix	fix(pipeline): Fix 3 NULL-target bugs, auto-generate package.nix (#93)	87	235	80	Config, Docs, Other, R Source
2026-03-14	Bug Fix	fix(nix): Fix cachix signing key, rebuild Bioconductor-dependent targets	2	0	0	Other
2026-03-14	New Feature	feat(captions): Add dynamic captions to 34 table/plot targets	22	579	89	Other, R Source
2026-03-14	Bug Fix	fix(vignettes): Enforce zero-computation rule — 22 violations → 0	32	360	764	Other, R Source, Vignettes
2026-03-13	Bug Fix	fix(vignettes): Convert kable RDS to data.frames, fix telemetry eval guards	18	8	2	Other, Vignettes
2026-03-13	Bug Fix	fix(ci): Save data frames (not DT widgets) to RDS for Nix portability	3	0	0	Other
2026-03-13	Bug Fix	fix(vignettes): Use Quarto #\| eval syntax for pkgdown-banner chunks	11	44	11	Vignettes
2026-03-13	Refactoring	refactor(targets): Move Bioconductor packages to per-target declarations	11	35	17	Other, R Source, Vignettes
2026-03-13	New Feature	feat(vignettes): Add code provenance, kable→DT conversion, caption compliance	35	1004	437	CI/CD, Other, R Source, Vignettes
2026-03-13	Bug Fix	fix(vignettes): Skip NULL RDS in safe_tar_read, return invisible(NULL)	11	22	22	Vignettes
2026-03-13	Bug Fix	fix(glossary): Prevent double DT::datatable() wrapping in glossary-table chunk	1	3	1	Vignettes
2026-03-13	CI/CD	ci: Show quarto errors with quiet=FALSE, render individual vignettes in diagnostic	1	20	6	CI/CD
2026-03-13	CI/CD	ci: Add verbose quarto error diagnostics on build failure	1	14	1	CI/CD
2026-03-13	Bug Fix	fix(vignettes): Strip Nix paths from DT widgets, auto-wrap data frames	25	66	28	CI/CD, Other, Vignettes
2026-03-13	CI/CD	ci: Add diagnostic quarto render step to debug build failure	1	17	0	CI/CD
2026-03-13	Bug Fix	fix(vignettes): Revert safe_tar_read placeholder, guard gene-report	11	12	56	Vignettes
2026-03-13	Maintenance	chore: Export vig_count_distribution_plot as ggplot RDS (513KB)	1	0	0	Other
2026-03-13	Bug Fix	fix(vignettes): Enable code eval in CI with RDS fallback	80	113	74	CI/CD, Other, R Source, Vignettes

Reproducibility

Session Info (click to expand)

Show code

sessionInfo()
#> R version 4.5.3 (2026-03-11)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 24.04.3 LTS
#> 
#> Matrix products: default
#> BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 
#> LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so;  LAPACK version 3.12.0
#> 
#> locale:
#>  [1] LC_CTYPE=C.UTF-8       LC_NUMERIC=C           LC_TIME=C.UTF-8       
#>  [4] LC_COLLATE=C.UTF-8     LC_MONETARY=C.UTF-8    LC_MESSAGES=C.UTF-8   
#>  [7] LC_PAPER=C.UTF-8       LC_NAME=C              LC_ADDRESS=C          
#> [10] LC_TELEPHONE=C         LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C   
#> 
#> time zone: UTC
#> tzcode source: system (glibc)
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> loaded via a namespace (and not attached):
#>  [1] vctrs_0.7.2         cli_3.6.5           knitr_1.51         
#>  [4] rlang_1.1.7         xfun_0.57           otel_0.2.0         
#>  [7] processx_3.8.6      targets_1.12.0      jsonlite_2.0.0     
#> [10] data.table_1.18.2.1 glue_1.8.0          prettyunits_1.2.0  
#> [13] backports_1.5.0     htmltools_0.5.9     ps_1.9.1           
#> [16] rmarkdown_2.30      tibble_3.3.1        evaluate_1.0.5     
#> [19] base64url_1.4       fastmap_1.2.0       yaml_2.3.12        
#> [22] lifecycle_1.0.5     compiler_4.5.3      codetools_0.2-20   
#> [25] igraph_2.2.2        pkgconfig_2.0.3     digest_0.6.39      
#> [28] R6_2.6.1            tidyselect_1.2.1    pillar_1.11.1      
#> [31] callr_3.7.6         magrittr_2.0.4      withr_3.0.2        
#> [34] tools_4.5.3         secretbase_1.2.0