PedigreeTool vs Evagene: standards-first versus research- and education-grade

Short version. PedigreeTool is a Stanford-backed browser pedigree application that positions itself as offering "the speed of sketching with standard scientific labels." Its strengths are NSGC-standard nomenclature with gender-inclusive symbols, ontology-linked search against HPO and MONDO, a rich export surface including GA4GH Phenopackets v2, and cloud storage — a set of capabilities that align very well with FAIR data principles and cross-institution research sharing. PedigreeTool's own website states plainly that it is not certified for clinical diagnostics, that auto-layout for complex families is still in development, and that clinical features are delayed to 2026. Evagene is a pedigree platform: BRCAPRO / MMRpro / PancPRO risk models, Mendelian calculators, AI-assisted draft summaries for educational / research review with bring-your-own-key LLMs, a REST/webhook/MCP platform layer, and a 230+ disease catalogue with ICD-10 and OMIM coding. Neither product is strictly a superset of the other. As of June 2026 Evagene also supports GA4GH Phenopackets v2 import and export, so the Phenopackets interchange that once clearly favoured PedigreeTool now round-trips between the two; PedigreeTool's remaining standards edge is its HPO-first capture depth and MONDO-native annotation. If your work is anchored in HPO/MONDO repositories and FAIR-first phenotype sharing, PedigreeTool remains a strong answer. If you are a research or teaching team that wants illustrative risk numbers, research- and education-grade reports, Phenopackets round-tripping, and a real integration platform, Evagene is the more appropriate tool.

This comparison is drawn from PedigreeTool's public website and documentation as of June 2026. If anything has since changed on their side, the PedigreeTool product pages supersede this article.

How the two products position themselves

PedigreeTool describes itself as combining "the speed of sketching with standard scientific labels." The product emphasises four things prominently: drag-and-drop canvas drawing, NSGC-standard nomenclature with gender-inclusive symbols, ontology-linked search against HPO (Human Phenotype Ontology) and MONDO (the Mondo Disease Ontology), and a broad export set (SVG, PNG, PDF, CSV, PED, JSON) including GA4GH Phenopackets v2. The Phenopackets alignment is meaningful — it places PedigreeTool inside the GA4GH FAIR-compliant data-sharing ecosystem, which matters for research consortia, collaborative rare-disease networks, and any group whose outputs need to flow into tools like Exomiser or LIRICAL.

PedigreeTool is also commendably honest about its current scope. Its own product pages state that auto-layout for complex family structures is still in development, that its clinical feature set is "delayed to 2026," that assisted-reproduction labelling is limited, and that the product is "not certified for clinical diagnostics." That is the kind of statement we always want to see on a research/clinical boundary product; it avoids ambiguity that could mislead a clinical buyer.

Evagene positions itself as pedigree drawing, management, and modelling. Its emphasis is on the pedigree as a clinical document that has to be produced at consultation speed, annotated with ICD-10 and OMIM-coded diseases from a curated 230+ catalogue, run through validated risk models (BRCAPRO, MMRpro, PancPRO, plus Mendelian AD/AR/XR), and then surfaced to downstream systems through a real platform: a scoped REST API, webhooks, an MCP server for AI agents, and an embeddable viewer. Evagene's AI layer is bring-your-own-key — you use your own Anthropic Claude or OpenAI GPT account (Fernet-encrypted at rest), so interpretation traffic goes where your information-governance process has already approved.

The headline difference is orientation. PedigreeTool orients to FAIR research data standards. Evagene orients to clinical service workflows. They share a browser, NSGC notation, and ontology-linked disease annotation; they diverge sharply on risk modelling, AI interpretation, and platform surfaces.

Feature-by-feature comparison

The matrix below summarises publicly advertised capabilities as of June 2026. A tick means the vendor publicly documents the feature. A dash means the feature is not publicly listed — it does not necessarily mean the feature is absent, especially on a beta product where documentation can lag the build.

Matrix compiled from publicly available product pages and documentation as of June 2026. "—" indicates the capability is not publicly advertised; it does not necessarily mean the feature is absent, particularly on a beta product.

Where PedigreeTool is stronger

It is fair to state this up front. PedigreeTool is built around the GA4GH FAIR data stack — HPO-first capture, MONDO-native annotation, Phenopackets v2 — and that orientation runs deeper than Evagene's. The gap has narrowed: as of June 2026 Evagene supports Phenopackets v2 import and export, offers educational HPO phenotyping, and cross-references its catalogue to MONDO, Orphanet, and DOID. But PedigreeTool's HPO-linked search and MONDO-native modelling sit at the centre of its product, whereas Evagene's HPO is educational documentation layered onto a pedigree-first tool. If your service works deeply with the Global Alliance for Genomics and Health ecosystem and your core workflow is HPO deep-capture driving candidate-gene prioritisation, PedigreeTool remains the more immediately aligned tool; the Phenopackets interchange itself now works either way.

PedigreeTool also ships with an academic credibility that matters in some procurement conversations. Its Stanford backing, explicit non-certification statement, and transparent roadmap (Research/Professional/Institutional tiers from April 2026, equity pricing for low-income countries) are signals of a serious, honest project. We respect that.

Where Evagene is stronger

Evagene is designed around research- and education-grade outputs, and that shows in several places PedigreeTool does not currently advertise. The integrated BayesMendel risk models (BRCAPRO, MMRpro, PancPRO) run directly on the pedigree data and produce an illustrative risk number for teaching and research review — without re-entering family history in a separate model runner. The Mendelian inheritance calculators cover autosomal dominant, autosomal recessive, and X-linked recessive patterns for monogenic conditions. Batch risk screening inverts the workflow: rather than "select condition X, run model," Evagene sweeps across the catalogue and surfaces conditions where family history crosses an illustrative threshold from published literature (not a recommendation). None of this is advertised by PedigreeTool; PedigreeTool's own site says clinical features are delayed to 2026.

The AI-assisted draft-summary layer is the second large gap. Evagene's BYOK LLM support (Anthropic Claude and OpenAI GPT, Fernet-encrypted), Analysis Templates with variable injection, and the MCP server exposing 27 tools to Claude Desktop, Claude Code, and any other MCP-compatible AI agent put Evagene in a different conversation for teams that are starting to use AI as part of report drafting. Beyond the MCP server, Evagene also offers an “Evagene Pedigree Builder” ChatGPT Custom GPT that turns a natural-language family-history description into a structured pedigree, and a Related Concepts educational correlation graph (1,100+ curated associations) linking diseases, genes, and findings as reference material — educational data, not risk analysis or diagnosis. As of June 2026, PedigreeTool publishes neither an MCP server nor a Custom GPT for pedigree building, and no other tool compared on this site does. If you just want a pedigree drawing you can export as Phenopackets, this does not matter. If you want AI to help draft an educational summary, it does.

The third gap is the platform layer. Evagene's REST API (scoped evg_ keys, SHA-256 hashed at rest, rate-limited, read/write/analyse scopes), webhooks (HMAC-SHA256 signed), and embeddable viewer (iframe/SVG/JavaScript) make Evagene usable from other systems without bespoke integration work. PedigreeTool's export surface is strong for file-based interchange; Evagene's platform surface is stronger for live system integration.

Standards, ontologies, and honest gaps

This is the section where we have to be frank in both directions. As of June 2026, the standards picture has changed: Evagene now supports GA4GH Phenopackets v2 import and export, educational HPO phenotyping, and MONDO / Orphanet / DOID cross-references alongside ICD-10 and OMIM. So the Phenopackets interchange that previously favoured PedigreeTool is no longer a one-sided gap. Where PedigreeTool still leads is depth of HPO-first capture and MONDO-native modelling at the centre of the product; Evagene's HPO and ontology cross-references are educational and research documentation layered onto a pedigree-first tool, not a clinical phenotype-driven diagnostic pipeline. Conversely, PedigreeTool's certification status is, by the vendor's own words, not "clinical diagnostic" — and Evagene is likewise positioned as a research and education tool, not a medical device. Neither tool should be treated as a clinical or diagnostic device.

A reasonable compromise for some services is to run both: PedigreeTool for research and FAIR-compliant export into downstream variant interpretation pipelines; Evagene for the clinical workflow, risk calculation, and reporting side. The shared ground is standard pedigree structure, which travels well via JSON and via PED-to-GEDCOM conversion.

Pricing and deployment

PedigreeTool is in free beta through March 2026. From April 2026, PedigreeTool's own site describes a tiered commercial model — Research (non-commercial), Professional (clinical/commercial), Institutional (admin dashboard) — with equity pricing for low-income countries. Exact numbers should be confirmed on PedigreeTool's pricing page, which supersedes this article. Deployment is cloud SaaS with no credit card required during beta.

Evagene is in Alpha and free via a waiting list at evagene.com. Pricing for general availability has not been published. Deployment is browser-based cloud; the platform surface (REST, webhooks, MCP, embedded viewer) means Evagene can sit inside another clinical system rather than being the only place the pedigree is accessed from.

When to choose PedigreeTool

• Your workflow is HPO-first at depth: phenotype deep capture driving candidate-gene prioritisation for downstream variant-interpretation pipelines (Exomiser, LIRICAL, consortium repositories). Both tools now read and write GA4GH Phenopackets v2, so the interchange itself is no longer the deciding factor — the depth of HPO-first capture is.
• You use MONDO as your disease ontology.
• You are a research service and need FAIR-compliant interchange, not validated clinical risk numbers.
• Your institution values Stanford-adjacent academic backing and the explicit non-clinical-certification posture.
• Your pedigree needs are simpler (straightforward family structures, not complex multi-generational consanguinity).

When to choose Evagene

• You run a clinical genetics service and need validated risk models (BRCAPRO, MMRpro, PancPRO, Mendelian) rather than phenotype export.
• AI-assisted report drafting using your own LLM keys is part of how your service wants to work.
• You need programmatic pedigree access via REST API, webhooks, MCP, or an embeddable viewer for EHR and patient-portal integration.
• You build pedigrees live during consultation and want gesture drawing.
• You need consanguinity detection, a karyogram viewer, and batch risk screening across a curated disease catalogue.
• You want a research- and education-grade pedigree platform with risk models, AI-assisted draft summaries, and a real integration platform, while keeping a clearly non-diagnostic posture.

Migrating from PedigreeTool to Evagene

PedigreeTool exports JSON, CSV, PED, PNG, SVG, PDF, and Phenopackets v2. Evagene imports GA4GH Phenopackets v2, GEDCOM 5.5.1, JSON, XEG, 23andMe genotype/traits/health, and pedigree images via OCR. The cleanest migration path is now Phenopackets-to-Phenopackets: a PedigreeTool Phenopacket carries individuals, relationships, and HPO phenotype features straight into Evagene's import, where the HPO features land in Evagene's educational HPO layer. JSON-to-JSON (a short schema mapping where individual/parent relationships transfer one-for-one) and PED-to-GEDCOM (the pedsuite R package has utilities, or a hand-written converter is a few dozen lines) remain available. MONDO annotations map to Evagene's catalogue, which carries MONDO, Orphanet, DOID, ICD-10, and OMIM cross-references; for clinical phenotype-driven workflows, remember that Evagene's HPO is educational and research documentation, not a diagnostic pipeline.

For services running both tools in parallel, Evagene's GEDCOM import makes a weekly or monthly bulk sync practical. For services that have never used Evagene but want to try, the pedigree-image OCR feature means you can bring an existing PNG or SVG from PedigreeTool directly into Evagene without any conversion step at all.

Frequently asked questions

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