Ask Questions, Get Insights
Conversational Lung
Biology AI
Perform complex multiomics analyses through natural language. Integrate single-cell RNA-seq, spatial transcriptomics, pathway enrichment, and literature research—no coding required. Accelerate discovery with publication-ready results.
About LungChat
Democratizing access to complex lung biology analysis
LungChat democratizes access to advanced multiomics analysis for lung biology research. Ask questions in natural language and receive publication-ready visualizations, data tables, and biological insights. Seamlessly combine single-cell RNA-seq data across 40+ studies, spatial transcriptomics from Xenium and Visium platforms, pathway enrichment from 120+ databases, and literature synthesis—all without writing a single line of code.
Whether you're identifying disease-specific cell signatures, validating findings across datasets, exploring spatial niches in tissue, or contextualizing discoveries through pathway and literature analysis, LungChat accelerates your research workflow while ensuring full reproducibility with complete parameter tracking.
Scientific Capabilities
Unleashing new possibilities for lung biology research
Comprehensive Single-Cell Analysis
Query 2.8M+ cells across 40+ studies covering normal lung, development, and 15+ diseases (IPF, COPD, COVID-19, BPD, cancer). Generate publication-ready UMAPs, heatmaps, violin plots, volcano plots, and differential expression analyses. Perform cross-dataset comparisons to identify conserved vs. disease-specific signatures with automatic marker gene discovery.
Spatial Transcriptomics Integration
Analyze spatial data from Xenium and Visium platforms to map cellular niches and spatial patterns in tissue context. Validate single-cell findings spatially and perform cross-platform correlation analysis for robust validation. Explore cell-cell communication networks and spatial neighborhood enrichment.
Functional Enrichment & Literature Synthesis
Perform pathway enrichment using 120+ databases (GO, KEGG, Reactome, disease ontologies) to identify biological processes, molecular functions, and disease associations. Synthesize findings from literature to contextualize discoveries and connect pathways to disease mechanisms.
LungMAP Database Integration
Query the LungMAP consortium database through natural language to access comprehensive lung development and disease resources. Discover datasets, explore sample demographics, retrieve gene lists from computational analyses, and perform cross-species comparisons for developmental trajectory analysis.
Custom Computational Analysis
Execute custom Python or R code in a secure sandbox for novel analyses, statistical computations, data transformations, and custom visualizations. Process TSV/CSV files, perform statistical tests, and create publication-quality plots tailored to your specific research questions.
Reproducibility & Provenance
Every analysis generates publication-ready figures (PNG/PDF), data tables (TSV), and complete parameter logs (JSON) ensuring full reproducibility and scientific rigor. All outputs are downloadable for publication, sharing, and exact replication of analyses.
Our Team
Meet the researchers behind LungChat
Frequently Asked Questions
Find answers to common questions about LungChat
LungChat integrates single-cell RNA-seq, spatial transcriptomics, functional enrichment, and literature research in a unified natural language interface. Unlike traditional tools that require coding expertise, LungChat enables researchers to perform complex multiomics analyses through conversational queries, while ensuring full reproducibility with complete parameter tracking and publication-ready outputs.
LungChat integrates 2.8M+ cells from 40+ single-cell RNA-seq studies covering normal lung, development, and 15+ disease states (IPF, COPD, COVID-19, BPD, cancer). Datasets include the Human Lung Cell Atlas (HLCA), fetal development atlases, and disease-specific cohorts. Spatial transcriptomics data includes Xenium and Visium platforms with multi-resolution annotations for tissue niches and cellular communication analysis.
Yes, LungChat is freely available for research purposes. To ensure fair access and system stability, each user can submit up to 15 queries per day and 50 queries per week.
Every analysis generates publication-ready figures (PNG/PDF), data tables (TSV), and complete parameter logs (JSON) containing all analysis parameters, dataset identifiers, and tool configurations. This ensures full provenance tracking and allows anyone to reproduce the exact analysis, meeting the highest standards of scientific reproducibility.
Currently, LungChat works with pre-integrated datasets from the LungMAP consortium and published studies. Support for user-uploaded datasets is planned for future releases. Contact us if you have specific datasets you'd like integrated or if you're interested in collaborating.
Research Paper
Our preprint describing LungChat's capabilities and scientific applications is coming soon.
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