TNMplot: differential gene expression analysis in Tumor, Normal, and Metastatic tissues.

The pan-cancer analysis page displays the expression range for a selected gene across all tissues using RNA Seq data from normal and cancer tissues.
red*: Mann-Whitney p<0.05 and
expression >10 in tumor or normal

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Database setup:
TNMplot includes 56,938 unique samples:
from GEO, GTex, TCGA, and TARGET databases.
This includes 15,648 normal, 40,442 tumor, and 848 metastasis samples.
Gene summary:

Copyright ©: TNMplot.com, 2021-2025
Check our other webtools: http://www.kmplot.com ; http://www.rocplot.com ; https://www.cancerhallmarks.com/
The pan-cancer heatmap analysis page displays log2 FC values of tumor/normal RNA-Seq data, red color represents higher expression in tumor, while the blue color indicates higher expression in normal tissues. The sizes of the circles are inversely proportional to the adjusted P values.
Please select at least 2 genes, the maximal number of genes allowed simultaneously is is 100. To paste multiple gene names please use capital names separated with space (e.g.: TOP2A MKI67 PIK3CA).

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1. Overview

TNMplot v2 is an advanced web-based platform designed for transcriptomic analysis, integrating RNA-Seq and gene-chip data from 57 thousand samples. It facilitates differential gene expression analysis across normal, primary tumor, and metastatic tissues, supporting over 20 tumor types with publication-ready visualizations. The new TNMplot v2 introduces stage-specific analysis, multi-gene analysis, correlation analysis tools, and expanded visualization features.

2. Features

- The pan-cancer analysis page displays the expression range for a selected gene across all tissues using RNA Seq data from normal and cancer tissues.

- The pan-cancer dot matrix analysis page displays log2 FC values of tumor/normal RNA-Seq data, red color represents higher expression in tumor, while the blue color indicates higher expression in normal tissues. The sizes of the circles are inversely proportional to the adjusted P values.

- TN-plot: the Normal and Tumor analysis page provides detailed analysis for a selected gene in a selected tissue type using RNA-seq and gene chip based data.

- TNM-plot: The Normal, Tumor and Metastatic analysis page provides detailed analysis for a selected gene in a selected tissue type using RNA-Seq and gene chip based data.

- Multi-Gene Analysis: Compare multiple genes simultaneously using density plots and box plots in both RNA-seq and gene chip datasets.

- Targetgram analysis: provides an overview of the selected gene set in the selected tissue using gene chip and RNA-Seq based data, the size of the segments represent the mean values, length of the dashed lines represent the median values of each types.

- Gene Signature Analysis: Analyze predefined gene signatures and their expression patterns. This papge page calculates the means of the selected gene signature across each patient one by one and provides a summary plot.

- Gene vs. Gene Correlation: Compare the correlation of two selected genes using multiple correlation methods in the selected tissue type.

- Correlation Matrix: Analyze relationships between multiple genes, and explore the correlation matrix of a selected gene set in the selected tissue type

- Correlation Profile Analysis: Explore correlation network for a selected gene by browsing all the genes showing correlation with the input gene in the selected tissue type.

- Stage-Specific Analysis: Investigate gene expression across different tumor stages.

- Functional analysis: perform GO or KEGG enrichment analysis

3. Data Sources

TNMplot v2 integrates transcriptomic data from multiple reputable sources:
- Genomic Data Commons (GDC): RNA-seq data from TCGA (adult tumors) and TARGET (pediatric tumors).
- Genotype-Tissue Expression (GTEx): Normal reference tissues.
- NCBI Gene Expression Omnibus (GEO): Manually curated gene chip datasets (>33,000 samples).

4. Performing an Analysis

Choose the dataset type (RNA-seq or gene-chip).

Select a gene from the input field.

1. Overview

TNMplot v2 is an advanced web-based platform designed for transcriptomic analysis, integrating RNA-Seq and gene-chip data from 57 thousand samples. It facilitates differential gene expression analysis across normal, primary tumor, and metastatic tissues, supporting over 20 tumor types with publication-ready visualizations. The new TNMplot v2 introduces stage-specific analysis, multi-gene analysis, correlation analysis tools, and expanded visualization features.

2. Features

- The pan-cancer analysis page displays the expression range for a selected gene across all tissues using RNA Seq data from normal and cancer tissues.

- The pan-cancer dot matrix analysis page displays log2 FC values of tumor/normal RNA-Seq data, red color represents higher expression in tumor, while the blue color indicates higher expression in normal tissues. The sizes of the circles are inversely proportional to the adjusted P values.

- TN-plot: the Normal and Tumor analysis page provides detailed analysis for a selected gene in a selected tissue type using RNA-seq and gene chip based data.

- TNM-plot: The Normal, Tumor and Metastatic analysis page provides detailed analysis for a selected gene in a selected tissue type using RNA-Seq and gene chip based data.

- Multi-Gene Analysis: Compare multiple genes simultaneously using density plots and box plots in both RNA-seq and gene chip datasets.

- Targetgram analysis: provides an overview of the selected gene set in the selected tissue using gene chip and RNA-Seq based data, the size of the segments represent the mean values, length of the dashed lines represent the median values of each types.

- Gene Signature Analysis: Analyze predefined gene signatures and their expression patterns. This papge page calculates the means of the selected gene signature across each patient one by one and provides a summary plot.

- Gene vs. Gene Correlation: Compare the correlation of two selected genes using multiple correlation methods in the selected tissue type.

- Correlation Matrix: Analyze relationships between multiple genes, and explore the correlation matrix of a selected gene set in the selected tissue type

- Correlation Profile Analysis: Explore correlation network for a selected gene by browsing all the genes showing correlation with the input gene in the selected tissue type.

- Stage-Specific Analysis: Investigate gene expression across different tumor stages.

- Functional analysis: perform GO or KEGG enrichment analysis

3. Data Sources

TNMplot v2 integrates transcriptomic data from multiple reputable sources:
- Genomic Data Commons (GDC): RNA-seq data from TCGA (adult tumors) and TARGET (pediatric tumors).
- Genotype-Tissue Expression (GTEx): Normal reference tissues.
- NCBI Gene Expression Omnibus (GEO): Manually curated gene chip datasets (>33,000 samples).

4. Performing an Analysis

Choose the dataset type (RNA-seq or gene-chip).

Select a gene from the input field.

Select the comparison type (e.g., normal vs. tumor, tumor vs. metastatic).

Generate visualizations and download results in publication-ready formats.

5. Advanced Functionalities

- Stage Comparison Analysis: Select a tumor type and analyze gene expression across stages I-IV.
- Multi-Gene Input: Simultaneously analyze multiple genes within a dataset.
- Correlation Analysis: Investigate relationships between genes within selected tissue types.
- Gene Signature Analysis: Evaluate expression trends of predefined gene sets.

6. System Requirements

- Supported Browsers: Chrome, Firefox, Edge, Safari.
- No software installation required (runs directly in the browser).

7. Data Privacy & Compliance

- GDPR Compliance: no personal data is stored.
- Cookie Policy: The website implements a cookie consent system where non-essential cookies are only set after user approval.

8. Support & Contact

For inquiries, bug reports, or support, contact:
- gyorffy@kmplot.com

9. Citation

If you use TNMplot in your research, please cite:
- Bartha Á, Győrffy B. TNMplot.com: A Web Tool for the Comparison of Gene Expression in Normal, Tumor, and Metastatic Tissues. *Int J Mol Sci.* 2021; 22(5):2622.

10. Future Development

TNMplot will continue to be maintained and expanded. Future updates may include:
- Additional tumor types and dataset expansions.
- New analytical methods for biomarker discovery.

11. Licensing

This website is free and open to all users, and there is no login requirement.