Moon helps diagnosing patients at:

Pinpointing variant

What is Moon?

Moon is an innovative software package that autonomously returns provisional diagnoses for rare diseases from NGS data using artificial intelligence (A.I.). Moon reduces the time needed for filtering and prioritising variants from days or weeks to mere minutes.

Diagnosing rare diseases can be like searching for a needle in a haystack.
When interpreting exome data for rare disease diagnostics, geneticists must identify the one or two mutations responsible for the patient’s condition hidden amongst 40,000 variants. This process takes between 20 and 40 hours when performed by highly skilled staff using specialised software (Wenger et al. 2016). This is prohibitively slow for many clinical applications.

Moon changes all this.

Magnet pulling needle from haystack

How does Moon work?

Geneticists upload NGS data (SNV/CNV) as a standard VCF file (e.g. directly from GATK) and they enter the patient's symptoms, gender and age of onset.
Moon takes this input and, using proprietary A.I. algorithms and a proprietary disorder model, suggests the causal variant in 2 minutes for WES and in 5 minutes for WGS. For each suggested candidate variant, a wide range of annotations are shown, thereby providing scientific evidence for Moon's choices. The results can then easily be verified and reported.

2-minute demo

Moon was honoured with a Best of Show Award at Bio-IT World Expo 2018 in Boston. The Best of Show program relies on a panel of expert judges from academia and industry who screen eligible new products and hear presentations from the finalists on site. Judges considered 46 new products and viewed presentations on site from 18 finalists.

Bio-IT Best of Show Winner 2018

How does Moon perform?

We tested Moon using 30 real-life single exome cases (without family data) that had previously been solved by our expert geneticists. The cases were previously unknown to Moon, and the software had not been trained on the cases in any way. Moon successfully solved 90% of these cases, with the causal variant appearing at the top of Moon’s list of candidate variants. In 100% of the cases, the causal variant was listed in Moon's top 3! For cases with family data available, Moon performs even better.

See how Moon compares to Exomiser:

Download White Paper
fast rocket


Rapid exome sequencing and interpretation can be crucial in the acute care of infants with genetic diseases in neonatal and paediatric intensive care units. Moon can go from standard VCF to a shortlist of provisional diagnoses in a ground-breaking 2 minutes for WES data, and in 5 minutes for WGS data. As such, Moon can be instrumental for this new wave of time-sensitive NGS-based diagnostics. Moon’s fast analysis times contributed to a new world record for fastest genome diagnosis, set by researchers at Rady Children’s Hospital in San Diego.

wallet (cost-efficient)


By reducing manual analysis time from between 20 and 40 hours per exome interpretation (Wenger et al. 2016) to less than an hour, Moon can potentially save between 19 and 39 hours of labor. The additional expert time that becomes available by using Moon, can be highly valuable for in-depth analysis of difficult, unsolved cases.

up to date

Up to date

Current software packages allow their users to define pipelines which are then applied to every exome analysed. However, because new gene-phenotype correlations are published every day, these pipelines quickly become outdated. Despite this, the gene panels used by these pipelines often remain untouched for months or even years. Moon is different in that it automatically scans the literature on a daily basis, integrating new scientific insights as they are published. As a result, Moon always gives you the best chance of reaching a diagnosis.



Since Moon can re-run analyses unsupervised, it's the perfect tool to re-run older analyses. Patients for whom no diagnosis is available today, might be diagnosable next month. Or next year. With Moon, infinite interpretation becomes a reality as re-running analyses is easy, fast and cheap.



While array-based methods have long been the standard to detect pathogenic CNVs, the relatively low resolution only allows to detect CNVs of approximately 20,000 base pairs in size or larger. Since the majority of CNVs in the human genome are smaller, this means that about 80% of all human CNVs are missed with the traditional approach. NGS-based CNV detection provides a solution to this problem, as CNVs as small as 100 base pairs can be detected with this method. Fast interpretation of these called CNVs can now be performed with Moon.
Moon’s automated filtering and ranking algorithms quickly guide you to the relevant CNVs for your patient’s phenotype. Moon can even detect relevant combinations of SNVs and CNVs, as SNV and CNV analyses are performed simultaneously. Finally, the rich CNV annotations and automated reporting allow for easy manual review of the Moon results.



Moon is deployed in ISO27001 or HIPAA compliant data centres that are always located in the customer’s country. That way, genetic data remains in the country where it has been generated. Moon runs on dedicated physical servers that adhere to the highest security standards and are operated in compliance with HIPAA and GDPR. At the application level, Moon offers two factor authentication, making sure that only your lab members can access Moon.

  • HIPAA compliant
  • GDPR compliant
  • two factor authentication

Automated Report

Not content to reduce the time to answer to just a few minutes, Moon squeezes even more time out of the process via natural language generation (NLG) technology to automatically write a first draft of the diagnostic report. This draft can then be edited.



Moon offers an easy-to-use REST API to import NGS and patient data, run analyses and retrieve results. As such, Moon can be easily integrated into any existing pipeline.

Free Moon trial

Give Moon a try with your own samples.
Click "Try now" for a web-based demo and a Moon trial account that will allow you
to analyse your own WES or WGS data.

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