pretty_name: SampleExplorer databases (ARCHS4 v2.7, release 1)
language:
- en
tags:
- RNA-seq
- GEO
- ARCHS4
- gene-set-search
- transcriptomics
- SampleExplorer
size_categories:
- 1M<n<10M
SampleExplorer databases (ARCHS4 v2.7, release 1)
Databases for SampleExplorer: one SQLite file per species. Each is a single file with nothing to unzip. This repository is the home of the files: every release is a tag here, and the desktop app's catalogue points at these tags. Check a download against the sha256 below.
| File | Species | Studies | Samples | Size | sha256 |
|---|---|---|---|---|---|
sampleexplorer-human-v2.7-r1.sqlite |
human | 38,761 | 1,098,771 | 1,556,414,464 bytes (1.6 GB) | ba3c7446968d719c965241dd3dcc16a040257976c5037e7026d345e7fd3f488c |
sampleexplorer-mouse-v2.7-r1.sqlite |
mouse | 40,620 | 1,225,044 | 1,717,370,880 bytes (1.7 GB) | 852056fff702f0cad8e39ccd8d81814a81d6529d30ab12647886a3e35b14f530 |
Download
With the Hugging Face CLI (resumable, checks the hash for you):
uvx --from huggingface_hub hf download Wlchin/sampleexplorer-databases sampleexplorer-human-v2.7-r1.sqlite --repo-type dataset --local-dir .
uvx --from huggingface_hub hf download Wlchin/sampleexplorer-databases sampleexplorer-mouse-v2.7-r1.sqlite --repo-type dataset --local-dir .
From Python:
from huggingface_hub import hf_hub_download
path = hf_hub_download("Wlchin/sampleexplorer-databases", "sampleexplorer-human-v2.7-r1.sqlite",
repo_type="dataset", revision="r1")
With curl (resumes with -C -):
curl -L -C - -o sampleexplorer-human-v2.7-r1.sqlite https://huggingface.co/datasets/Wlchin/sampleexplorer-databases/resolve/r1/sampleexplorer-human-v2.7-r1.sqlite
Check a download with shasum -a 256 <file> on macOS and Linux, or certutil -hashfile <file> SHA256 on Windows.
Use
Open a file in the SampleExplorer desktop app with Locate database file…, or read it with any sqlite3.
Open both files to search across species.
What each file holds
- GEO study and sample text
- the per-sample gene index for gene-set search
- MiniLM text vectors and the MiniLM model
- the response bases for the Same response search
- the BM25 keyword index
- MedCPT article vectors and the MedCPT query encoder
- the 50 MSigDB Hallmark pathway sets and the pathway bank behind Compare pathways
The file's meta table records the ARCHS4 version, the build rules, content hashes and the sha256 of every bundled model
and of the pathway sources.
Source data
Expression and sample metadata come from ARCHS4 v2.7 (Lachmann et al., 2018, Nature Communications 9:1366), which reprocesses public RNA-seq from GEO and SRA. Study and sample text come from GEO. Please cite ARCHS4 and GEO alongside SampleExplorer when you use these files.
Pathway gene sets: sources and attribution
The pathway data (the pathway_sets table, the pathway_bank array and meta pathways) come from two sources:
- MSigDB Hallmark v2023.2.Hs (
h.all.v2023.2.Hs.symbols.gmt, 50 sets) from the Molecular Signatures Database, UC San Diego and Broad Institute, under CC BY 4.0. Each set is kept as its genes in the file's gene universe, and the file stores directions computed from them; the set names are unchanged. Cite Liberzon et al., 2015, Cell Systems 1:417–425 (doi:10.1016/j.cels.2015.12.004) and MSigDB (Subramanian et al., 2005, PNAS 102:15545–15550). - MGI's mouse–human homology report (
HOM_MouseHumanSequence.rpt, dated 2026-10-28), mouse file only: it maps the human sets to one-to-one mouse orthologues. From Mouse Genome Informatics, The Jackson Laboratory; cite Baldarelli et al., 2024, Genetics 227:iyae031 (doi:10.1093/genetics/iyae031).
The full notice, with the changes made, the sha256 of both source files and the MGI data citation, is in
LICENSES/CC-BY-4.0-MSigDB-Hallmark.txt.
Bundled models and their licences
Two text encoders are stored inside each file as ONNX exports, so the app needs no PyTorch and no separate download. Converting them to ONNX and bundling them is the only change made to them.
| Model | Used for | Source | Licence |
|---|---|---|---|
| paraphrase-MiniLM-L6-v2 | search by meaning | sentence-transformers/paraphrase-MiniLM-L6-v2, revision c9a2bfebc254878aee8c3aca9e6844d5bbb102d1 (Reimers & Gurevych, UKP Lab) |
Apache-2.0 |
| MiniLM base weights | base of the above | Microsoft MiniLM | MIT |
| MedCPT query encoder | keyword + semantic search | ncbi/MedCPT-Query-Encoder (Jin et al., 2023) | public domain (US Government work) |
| MedCPT article encoder | article vectors (vectors stored, encoder not bundled) | ncbi/MedCPT-Article-Encoder | public domain (US Government work) |
The Apache-2.0 licence text is in LICENSES/Apache-2.0.txt and the MIT text in LICENSES/MIT-MiniLM.txt in this
repository, as the Apache licence requires for redistribution.
Versions
Each release is a tag (r1, r2, …) on this repository. A released file is never changed: a new build gets a new file
name (-r2), a new commit and a new tag, and the old tag keeps serving the old bytes. Download by tag or by commit
hash, not from main, so a link always returns the same file. Every push is a commit, so the full history of the
repository is the release history.
Citation
Until the paper is out, cite this repository by its DOI (generated from the repository settings; added here once minted) and the release tag:
SampleExplorer databases (ARCHS4 v2.7, release 1), tag
r1. Hugging Face. DOI: to be added.
How to cite the paper: added when the paper is published.