What kind of Research Questions?

What kind of Research Outputs?

1. Pairwise Clustermap

Input: Cases in Face2Gene CLINIC (grouping is possible).


Output: Pairwise Clustermap where we compare each case to every case in the cohort (x and y axes) plus every image in our control gallery (4.3k photos); the number in the box is the similarity rank achieved.


Low numbers mean that the cohort is more similar amongst itself than compared to our control gallery.

A clustering algorithm is applied, and the resulting dendogram can be explored to check for subclusters (e.g. 6 subjects on the right vs 28 on the left).

2. tSNE or PCA visualization

Input: Cases in Face2Gene CLINIC (grouping is possible), with associated relevant clinical information.


Output: Dimensionality reduction is applied to the photo vectors (tSNE or PCA) and a 2D or 3D representation in the Clinical Face Phenotype Space (CFPS) is obtained. Smaller distances in CFPS translate to more similar facial phenotypes. A confidence ellipse per cluster is also included.


The top-N similar syndromes in our database may also be represented (potential confounding syndromes/patient matching analyses).


Each data point can be matched to a subject via case ID, and additional relevant information may be included in the hover box.

3. Statistical Similarity Analysis

Input: Independent samples of age and gender-matched cases in Face2Gene CLINIC. FDNA may provide a control group.


Output: First, the similarity is computed between every pair of cases – intra and inter-cohorts.


Assumption checks are used to determine parametric/nonparametric testing: Normal distribution, equal variance and outliers.


Adequate pairwise tests are then used to compare every two groups, correcting for multiple comparisons by applying the Bonferroni correction.

A boxplot visualization of the groups is also generated. Additional statistical information per group is shown on hover.

Would you like to know more?

Contact us at research@fdna.com

Check out our Research FAQs

Face2Gene User Community Includes Users From:

  • Using Face2Gene to reference all my department’s cases, share information with my colleagues and quickly look up relevant information in the London Medical Databases Online saves me hours of work every week and allows me to focus on my patients.

    Dr. Ibrahim Akalin

    Assoc. Prof. Ibrahim Akalin, MD, Medical Geneticist from the Istanbul Medeniyet University, Istanbul, Turkey

  • FDNA’s game-changing technology introduces an objective computer-aided dimension to the “art of dysmorphology”, transforming the analysis into an evidence-based science.

    Dr. Michael R. Hayden

    Chairman of FDNA’s Scientific Advisory Board & Steering Committee and Editor in Chief of Clinical Genetics

  • FDNA is developing technology that has the potential to help so many physicians and families by bringing them closer to a diagnosis- there are literally millions of individuals with unusual features around the world that lack a diagnosis and therefore lack information on natural history, recurrence risk and prevention of known complications.

    Dr. Judith G. Hall

    Professor Emerita of Pediatrics & Medical Genetics UBC & Children's and Women's Health Centre of BC

  • FDNA has been “right on the money”, providing me with relevant, accurate and insightful information for differential diagnoses.

    Dr. Cynthia J.R. Curry

    Professor of Pediatrics UCSF, Adjunct Professor of Pediatrics Stanford

  • I am excited to be a part of the FDNA community, promoting broad information sharing with my peers to amplify the scientific and clinical value of our community’s accumulated knowledge for the purpose of efficiently diagnosing individuals with rare genetic disorders.

    Dr. Karen W. Gripp

    Chief, Division of Medical Genetics A.I. duPont Hospital for Children

  • FDNA's idea of incorporating several dysmorphology resources (OMIM, GeneReviews), supported by their visual analytic technology, will be able to improve researching of genetic syndromes - all within a single mobile app.

    Dr. Chad Haldeman-Englert

    Assistant Professor Pediatrics at Mission Fullerton Genetics

  • Given the advancement of visual analytical technology, it’s about time Dysmorphology is supported with computational capabilities and moving this to mobile support, is simply the next logical step.

    Dr. Chanika Phornphutkul

    Associate Professor of Pediatrics Director, Division of Human Genetics Department of Pediatrics Warren Alpert Medical School of Brown University

  • Having an archive of cases easily accessible from my mobile device anytime and anywhere is a long-time unmet need.

    Dr. Lynne Bird

    Rady Children's Specialists of San Diego

  • FDNA's solution is a huge leap forward for dysmorphology. It saves me significant time when I’m evaluating patients in my clinic and provides me with insightful tools that help me generate a differential diagnosis.

    Dr. David A. Chitayat

    Head of the Prenatal Diagnosis and Medical Genetics Program at Mount Sinai Hospital, Toronto

  • Shortly after learning about Face2Gene, I’ve started to incorporate this amazing tool into my workflow. Soon enough, Face2Gene’s analysis flushed out references that I would not have considered for several of my patients, which turned out to be their correct diagnosis

    Dr. Zvi U. Borochowitz

    Chairman (Retired) of The Simon Winter Institute for Human Genetics at Bnai-Zion Medical Center, Technion-Rappaport Faculty of Medicine

  • The Unknown Forum from Face2Gene is a great community platform for exchanging opinions regarding undiagnosed cases. It is straightforward to use and safe for exchange of medical data, thanks to the efforts of its developers and to the involvement of geneticists worldwide.

    Dr. Oana Moldovan

    Clinical Geneticist at the Hospital Santa Maria, CHLN, Lisbon, Portugal