Compare across species, with context
Move from genes to cell populations without losing sight of orthology, sampling, tissue identity, or evolutionary distance. Each entry point answers a distinct comparative question.
Harmonization supports comparison; it does not erase biology or bias
Cross-species single-cell analysis is most informative when the unit of comparison is explicit. Gene-level questions require defensible ortholog mapping; cell-level questions require compatible tissue and cell-state definitions. Age, sex, sampling depth, protocol, and cohort design can still shape an apparent difference after a shared processing workflow.
Use these tools to discover patterns and frame hypotheses. Interpret correlations as associations, distinguish expression shifts from composition shifts, and validate important conclusions against study metadata and independent evidence.
Choose the endpoint that matches your question
The four analytical routes are deliberately separated: two operate on genes and two on cell populations. Start with the biological endpoint, then inspect the available controls and metadata inside the selected tool.
Gene Comparative Analysis
Inspect how an ortholog-mapped gene is represented across available species, tissues, and cell groupings. Use the visual summaries to locate conserved or divergent patterns.
Expression differences can reflect both biology and study design.
Open gene comparisonGene Correlation Analysis
Compare geneโgene co-variation patterns in the available data and ask whether an association is similar across biological contexts or species.
Correlation does not establish direct regulation or a shared mechanism.
Open gene correlationCell Comparative Analysis
Examine cell-population representation across available species, tissues, and groups while keeping annotation granularity and compositional constraints visible.
Observed proportions are conditional on capture, filtering, and annotation.
Open cell comparisonCell Correlation Analysis
Explore whether cell-population abundances co-vary across the available observations and compare those associations across species or tissue settings.
Co-variation can arise from shared sampling or composition as well as biology.
Open cell correlationPlace every cross-species result in the right frame
These two guides do not perform the four core comparisons. They help define what lifespan evidence means and whether a particular organism is a suitable experimental model for the question.
LifeSpan
Separate maximum-longevity records, population estimates, and experimental survival endpoints. Compare definitions and provenance before relating lifespan to molecular or cellular patterns.
Animal Model
Select models by causal question, tissue and cell biology, experimental timescale, endpoint, and intended translation rather than assuming one organism is universally representative.
From a focused question to a qualified result
Define the endpoint
Choose expression, co-expression, population abundance, or co-occurrence before inspecting the result.
Align the units
Check orthology, tissue, cell identity, age context, cohort design, and annotation granularity.
Inspect support
Review sample availability, transformations, uncertainty, and plausible technical or compositional effects.
Report the boundary
Record mapping and filters, avoid causal overreach, and validate important findings independently.