TransTEx expression groupings

(human · mouse)

A browser tool for looking up TransTEx transcript expression-group classifications across human tissues (GTEx) and a mouse body map, and downloading any filtered slice as CSV. The browser app reads TransTEx_dataset.parquet. Cancer data will be added separately later.

Available: https://pallavisurana1.github.io/TransTEx_datasets/

What's in it

The data comes from the TransTEx scoring method, which assigns every transcript to one expression group per resource based on how many tissues it is reliably expressed in.

Normal tissues (human GTEx, mouse body map) — five groups:

Class	Meaning
TSp	Tissue-Specific — reliably expressed in a single tissue
TEn	Tissue-Enhanced — expressed in 2 tissues up to 50% of tissues
Wide	Widespread — expressed in more than 50% of tissues
Low	Low or less expression — below the specificity threshold, some expression
Null	No / minimal expression across all tissues

Everything is at transcript / isoform level, mapped to genes.

Using the browser tool

Choose any number of tissues from Tissues and expression groups from Categories; then optionally filter by species or transcript/gene. Leaving a multi-select empty means “all”.

Results and CSV downloads are collapsed to one row per transcript and species. When the same transcript has more than one matching category or tissue, the distinct values are shown as comma-separated lists. This keeps, for example, multiple relevant tissues for the same transcript on one row.

Schema

The Parquet file uses this schema before the browser aggregates matching records for display and export:

transcript, gene_id, gene_name, tissue, category, species

• tissue — the tissue (e.g. testis, liver); it may be empty for non-tissue-specific categories
• category — the expression group (TSp/TEn/Wide/Low/Null)
• species — human or mouse

Data Citations

If you use this dataset or the associated methodologies, please cite the following publications:

🔬 Methods & Frameworks

• TransTEx Method (Human Transcriptome)

  Surana P, Dutta P, Davuluri RV. TransTEx: novel tissue-specificity scoring method for grouping human transcriptome into different expression groups. Bioinformatics 2024;40(8):btae475. 🔗 doi:10.1093/bioinformatics/btae475

• TSProm (Mouse Body-Map Groupings)

  Surana P, Dutta P, Papineni N, Sathian R, Zhou Z, Liu H, Davuluri RV. TSProm: deep learning framework to predict tissue-specific regulatory logic. NAR Genomics and Bioinformatics 2026;8(2):lqag050. 🔗 doi:10.1093/nargab/lqag050

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🌐 Software & Databases

• TransTEx Database: Database Link
• TransTEx R Package: GitHub Repository

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📊 Underlying Source Data

The datasets curated here are derived from the following foundational resources:

Data Type	Source Resource
Human Normal Tissue	GTEx Consortium (Version 8)
Mouse Tissue	Mouse Body Map (grouped via TSProm)