Rare Diseases

Discover the rarest variants in your NGS data.

Rare Diseases

The use of Next Generation Sequencing in the field of rare diseases is all about finding rare candidate mutations. Genalice’ patented highly accurate mapping and observational variant calling methods, offer a precise instrument to uncover these.


Embedded trio analysis reports Mendelian errors and allows for reliable De Novo variant detection. Trio analysis in Genalice Population further allows lower sequencing depths for parents and a complete full genome analysis takes just 1 hour on a small server.

Genalice Population has the ability to collect thousands of samples in a single repository and supports large scale analysis to find ‘the needle in the hay stack’.

Genalice solutions can be life changing in patient diagnostics by reducing processing time from days to hours, enabling clinicians to decide quickly on the best possible treatment.

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Pioneering an efficient migration of 13,000 whole genomes: Catching up with the latest human genome assembly.

Author: S. Graf et al. (University of Cambridge, United Kingdom)

The challenge: Migrating a dataset of 13,000 whole genomes focused on the identification of the genetic basis of rare diseases with emphasis on cardiovascular disorders to the latest human reference standard GRCh38.

The solution: Analysis of 13,000 whole genomes shows that GRCh38 delivers better coverage and significantly more variants without detriment to quality. Alignment and variant calling for GRCh38 was completed in 20 days using 10 compute nodes.



Comprehensive real life workflow for rapid diagnosis of critically ill children.

The challenge: Rare genetic conditions are frequent risk factors for, or direct causes of, organ failure requiring paediatric intensive care unit (PICU) support. There is therefore a need to provide a rapid genetic diagnosis to inform clinical management. To date, Whole Genome Sequencing (WGS) approaches have proved successful in diagnosing a proportion of children with rare diseases, but results may take months to report or require the use of equipment and practices not compatible with a clinical diagnostic setting.

The outcome: Using the Genalice system, the researchers were able to significantly reduce the processing time from raw sequence data (FASTQ format) to text files containing lists of variants from the reference sequence (VCF files) from up to 144 hours (using a standard GATK pipeline) to 60 minutes per trio. To ensure the increased processing speed did not adversely affect the accuracy of variant calls the researchers processed the Genome in a Bottle (GIAB) reference sample under exactly the same conditions as our RaPS samples.

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