Healthcare
19 columns
110 rows
8 formats

Gene Expression Profiling and RNA Sequencing

This dataset provides comprehensive RNA sequencing profiles, including gene expression quantification, differential expression analysis, pathway associations, fusion transcript detection, and molecular subtyping for each biological sample. It is designed for advanced research and clinical diagnostics, enabling biomarker discovery, disease classification, and pathway-driven insights in genomics.

last updated 2 Nov 2025
by GoMask

The brief that made it

Biomarker discovery for disease diagnosis and prognosis

Sample rows

preview · 8 of 110 rows · all 19 columns

sample_idstring	differential_expression_statusstring	adjusted_p_valuefloat	platformstring	sample_typestring	collection_datedate	gene_symbolstring	ensembl_idstring	expression_valuefloat	fold_changefloat	p_valuefloat	pathway_namestring	pathway_idstring	fusion_transcript_namestring	fusion_transcript_supportinteger	molecular_subtypestring	diagnosisstring	analysis_datedate	analyst_namestring
SMP00001	upregulated	0.0031	Illumina	tissue	2023-08-11	BRCA1	ENSG00000012048	80.2	9.8	0.0012	DNA Repair Pathway	KEGG:hsa03440	blank	blank	Luminal A	Breast Cancer	2023-08-13	Dr. A. Kim
SMP00002	not_significant	blank	Illumina	blood	2021-02-17	CD19	ENSG00000177455	24.7	blank	blank	B cell receptor signaling	KEGG:hsa04662	blank	blank	Normal	Healthy Donor	2021-02-19	R. Gomez
SMP00003	upregulated	0.021	BGISEQ	cell_line	2018-11-22	KRAS	ENSG00000133703	49.1	3.5	0.015	MAPK signaling pathway	KEGG:hsa04010	KRAS-ALK	32	KRAS-mutant	Colorectal Cancer Cell Line	2018-11-24	Cell Analysis Team
SMP00004	downregulated	0.046	Illumina	tissue	2022-04-06	TP53	ENSG00000141510	110.6	0.251	0.037	Cell cycle	KEGG:hsa04110	blank	blank	Triple Negative	Breast Cancer	2022-04-08	Dr. S. Lee
SMP00005	upregulated	0.018	PacBio	other	2024-01-18	NTRK1	ENSG00000198400	35.7	8.3	0.009	Neurotrophin signaling	KEGG:hsa04722	NTRK1-ETV6	77	Gene Fusion	Thyroid Cancer	2024-01-20	FusionSeq Team
SMP00006	downregulated	0.0071	Ion Proton	cell_line	2023-05-27	PTEN	ENSG00000171862	0.09	0.0002	0.0028	PI3K-Akt signaling	KEGG:hsa04151	blank	blank	PTEN-loss	Prostate Cancer Cell Line	2023-05-28	Dr. J. Wang
SMP00007	upregulated	0.016	Illumina	tissue	2019-03-14	EGFR	ENSG00000146648	56.8	12.6	0.0082	ErbB signaling pathway	KEGG:hsa04012	blank	blank	HER2+	Gastric Cancer	2019-03-16	J. Patel
SMP00008	not_significant	blank	Illumina	blood	2020-08-04	HBB	ENSG00000244734	18.4	blank	blank	Hemoglobin synthesis	REACT:R-HSA-123456	blank	blank	Normal	Volunteer	2020-08-06	M. Hardy
SMP00009	upregulated	0.0094	Illumina	cell_line	2022-09-30	ALK	ENSG00000171094	54.6	5.9	0.0038	Oncogenic signaling	REACT:R-HSA-6805567	ALK-EML4	120	ALK Fusion	Lung Cancer Cell Line	2022-10-02	FusionSeq Team
SMP00010	downregulated	0.049	Ion Torrent	other	2017-06-15	CDKN2A	ENSG00000147889	3.4	0.302	0.042	Cell cycle control	KEGG:hsa04115	blank	blank	Melanoma Subtype	Melanoma	2017-06-17	Melanoma Study Group
SMP00011	upregulated	0.00006	Ion Proton	tissue	2021-12-03	MYC	ENSG00000136997	99999.99	400	0.00001	Cellular proliferation	KEGG:hsa05206	blank	blank	MYC-amplified	Lymphoma	2021-12-06	Dr. L. Smith
SMP00012	not_significant	blank	Illumina	blood	2019-07-21	GATA1	ENSG00000107485	12.6	blank	blank	Erythropoiesis	KEGG:hsa04918	blank	blank	Normal	Healthy Donor	2019-07-22	Dr. P. Yoon
SMP00013	downregulated	0.099	Illumina	tissue	2022-11-09	ERBB2	ENSG00000141736	7.4	0.51	0.095	ErbB signaling pathway	KEGG:hsa04012	blank	blank	HER2+	Breast Cancer	2022-11-12	Dr. S. Lee
SMP00014	upregulated	0.000005	BGISEQ	cell_line	2020-04-20	BRAF	ENSG00000157764	100000	175.2	0.000001	MAPK signaling pathway	KEGG:hsa04010	blank	blank	BRAF-mutant	Melanoma Cell Line	2020-04-21	Dr. N. Rao
SMP00015	upregulated	0.028	PacBio	other	2024-03-02	EWSR1	ENSG00000065320	2.9	2.4	0.019	RNA processing pathway	REACT:R-HSA-72163	EWSR1-FLI1	245	Gene Fusion	Ewing Sarcoma	2024-03-04	FusionSeq Team
SMP00016	not_significant	blank	Illumina	tissue	2020-10-08	CDK4	ENSG00000135446	25.8	blank	blank	Cell cycle	KEGG:hsa04110	blank	blank	Luminal B	Breast Cancer	2020-10-09	J. Patel
SMP00017	upregulated	0.022	Ion Proton	cell_line	2021-05-11	NTRK3	ENSG00000140525	39.3	5.7	0.011	Neurotrophin signaling	KEGG:hsa04722	NTRK3-ETV6	11	Gene Fusion	Pediatric Glioma Cell Line	2021-05-12	FusionSeq Team
SMP00018	downregulated	0.032	Illumina	blood	2022-06-23	ALAS2	ENSG00000158578	33.6	0.16	0.025	Heme biosynthesis	KEGG:hsa00260	blank	blank	Normal	Healthy Donor	2022-06-26	M. Hardy
SMP00019	downregulated	0.15	Illumina	tissue	2024-02-14	BCL2	ENSG00000171791	3.2	0.56	0.12	Apoptosis	KEGG:hsa04210	blank	blank	Follicular Subtype	Lymphoma	2024-02-16	Dr. L. Smith
SMP00020	not_significant	blank	BGISEQ	cell_line	2018-09-12	CDK6	ENSG00000105810	8.9	blank	blank	Cell cycle	KEGG:hsa04110	blank	blank	Normal Cell Line	Healthy Cell Line	2018-09-15	Cell Analysis Team

What the 110 rows show

from the 110-row sample

Upregulated (differential expression status) stands out: mean adjusted_p_value is 0.01, against 0.06 for the rest.

0.02median adjusted_p_value
4sample types
19.3median expression_value
4.5median fold_change
0.01median p_value
90.5median fusion_transcript_support

Mean adjusted_p_value by differential_expression_status89 rows

adjusted_p_value89 rows, in bands of 0.03

Median 0.02, from 0.00 to 0.22.

platform110 rows · 6 values

Illumina48
PacBio19
Ion Proton17
BGISEQ14
Nanopore9
Ion Torrent3

19 columns by typefrom the column list below

string 12
integer 1
float 4
date 2

Columns

19 columns in three groups

blueprint · 19 columns
column	type	description	example
Text 12 columns
`sample_id`	string	Unique identifier for each RNA sequencing sampleunique	SMP00001
`sample_type`	string	Type of biological sample (e.g., tissue, cell line, blood)tissue · cell_line · blood · other	tissue
`gene_symbol`	string	Official gene symbol according to HGNC nomenclature	BRCA1
`ensembl_id`	string	Ensembl gene identifieroptional	ENSG00000012048
`differential_expression_status`	string	Indicates if the gene is differentially expressed in the sampleupregulated · downregulated · not_significant · optional	upregulated
`pathway_name`	string	Name of biological pathway associated with the geneoptional	DNA Repair Pathway
`pathway_id`	string	Unique identifier for the pathway (e.g., KEGG, Reactome)optional	KEGG:hsa03440
`fusion_transcript_name`	string	Name of detected fusion transcript (if any)optional	KRAS-ALK
`molecular_subtype`	string	Assigned molecular subtype based on expression profilingoptional	Luminal A
`diagnosis`	string	Clinical or research diagnosis associated with the sampleoptional	Breast Cancer
`analyst_name`	string	Name of the person or team who performed the analysisoptional	Dr. A. Kim
`platform`	string	Sequencing platform used (e.g., Illumina, Ion Torrent)6 platforms · optional	Illumina
Numbers 5 columns
`expression_value`	float	Normalized gene expression value (e.g., TPM, FPKM)0 or more	80.2
`fold_change`	float	Fold change of gene expression compared to control/referenceoptional	9.8
`p_value`	float	Statistical significance of differential expression0 to 1 · optional	0.0012
`adjusted_p_value`	float	Multiple testing corrected p-value (e.g., FDR)0 to 1 · optional	0.0031
`fusion_transcript_support`	integer	Number of supporting reads for the fusion transcript0 or more · optional	32
Dates and times 2 columns
`collection_date`	date	Date the sample was collectedoptional	2023-08-11
`analysis_date`	date	Date when RNA sequencing analysis was performedoptional	2023-08-13

Use it for

A healthcare dashboard
Adjusted_p_value by differential_expression_status and a breakdown of platform. Excel, Power BI or Tableau.
Why do the 50 upregulated rows have a mean adjusted_p_value of 0.01?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Samples110
SMP000010.0031upregula…
SMP00002not_sign…
SMP000030.021upregula…
A software demo
Believable samples with sample_type, collection_date and gene_symbol to fill a screen in front of a buyer.

This dataset110 rows19 columns

Yours1,000 rows19 columns

blueprint · gene-expression-profiling-and-rna-sequencing

Behind this dataset

Same schema. As many rows as you need.

These 110 rows came out of a blueprint — 19 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with

Sample ID unique per tissue or cell type
RNA sequencing platform: Illumina, PacBio Iso-Seq
Library type: total RNA, mRNA (poly-A), small RNA
Read depth and length
Gene-level expression: FPKM, TPM, or raw counts
Differentially expressed genes (DEG): tumor vs normal
Fold change and adjusted p-value (FDR)
Pathway enrichment analysis: KEGG, GO terms

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: gene-expression-profiling-and-rna-sequencing

What should your data show?

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Sample rows

What the 110 rows show

Columns

Use it for

A healthcare dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Healthcare

What should your data show?