Genome-Scale Variant Interpretation

Automated Radiation Dose Estimation

Mission Statement

MutationForecaster® ( is Cytognomix’s patented web-portal for analysis of all types of mutations (coding and non-coding), including interpretation, comparison and management of genetic variant data. It’s a fully automated genome interpretation solution for research, translational and clinical labs.

MutationForecaster® combines our world-leading genome interpretation software on your exome, gene panel, or complete genome (Shannon transcription factor and splicing pipelines, ASSEDA, Veridical) with the Cytognomix User Variation Database and  Variant Effect Predictor.  With our integrated suite of software products, analyze coding, non-coding, and copy number variants, and compare new results with existing or your own database.  Select predicted mutations  by phenotype using articles with CytoVisualization Analytics.  With Workflows,  automatically perform end-to-end analysis with all of our software products.

Download an 1 page overview of MutationForecaster®link .

You can now experience our integrated suite of genome interpretation products through a free trial of MutationForecaster®. Once you register, analyze datasets that we have analyzed in our peer-reviewed publications with any of our software tools.

Ionizing radiation produces characteristic chromosome changes. The altered chromosomes contain two central constrictions, termed centromeres, instead of one (known as dicentric chromosomes [DCs]). Chromosome biodosimetry is approved by the IAEA for occupational radiation exposure, radiation emergencies, or monitoring long term exposures.  In emergency responses to a range of doses, labs need efficient methods that identify DCs.

Cytognomix has developed  a novel approach to find DCs that is independent of chromosome length, shape and structure from different laboratories (paper: TBME).  The Automated Dicentric Chromosome Identifier and Dose Estimator (ADCI) software  works on multiple platforms and uses images produced by any of the existing automated metaphase capture systems found in most cytogenetic laboratories. ADCI is now available for for trial or  purchase (link).  Or contact us for details (pricing).

ADCI* uses machine learning based algorithms with high sensitivity and specificity that distinguish monocentric and dicentric chromosomes (Try the Dicentric Chromosome Identifier web app). With novel image segmentation, ADCI has become a fully functional cytogenetic biodosimetry system. ADCI takes images from all types of commercial metaphase scanning systems,  selects high quality cells for analysis, identifies dicentric chromosomes (removing false positives), builds biodosimetry calibration curves, and estimates exposures.  ADCI fulfills the criteria established by the IAEA for accurate triage biodosimetry of a sample in less than an hour. The accuracy is comparable to an experienced cytogeneticist. Check out our online user manual: wiki.

We find and validate mutations that others cannot with advanced,  patented genomic  probe and bioinformatic technologies. Cytognomix continues our  long track record of creating technologies for genomic medicine. We anticipate and implement the needs of the biomedical and clinical genomics communities.

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Latest Posts

March 31, 2017. New preprint on increased accuracy in radiation biodosimetry

Accurate Cytogenetic Biodosimetry Through Automation Of Dicentric Chromosome Curation And Metaphase Cell Selection Jin Liu, Yaking Li, Ruth Wilkins, Farrah Flegal, Joan H. M. Knoll, Peter K. Rogan. bioRxiv, doi: Abstract: Software to automate digital pathology relies on image quality and the rates of false positive and negative objects in these images. Cytogenetic biodosimetry […]

February 27, 2017. CytoGnomix finalizes contract with Government of Canada

CytoGnomix has finalized our contract with Public Works Government Services Canada under the Build in Canada Innovation Program. This agreement licenses the Automated Dicentric Chromosome Identifier (ADCI) to the Consumer and Clinical Radiation Protection Bureau at Health Canada and Canadian Nuclear Laboratories and provides on-site training to these labs. These biodosimetry reference labs will test […]

Jan. 28, 2017. New version of F1000Research paper on chemotherapy response in breast cancer

We have published a new version of: Predicting Outcomes of Hormone and Chemotherapy in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) Study by Biochemically-inspired Machine Learning. F1000Research 2017, 5:2124 (doi:10.12688/f1000research.9417.2) The revision addresses the comments of the reviewers and adds several new analyses and results. Among our findings was the discovery of significant batch effects that, respectively, differentiate gene expression […]

Jan. 23, 2017. Automated interpretation of digital pathology images is currently at an embryonic stage of development

Counting pixel area and pixel intensities (stained antibodies, DNA or RNA) does not determine the identities of the cellular objects that are labeled. The challenge is that every microscope field exhibits different morphology, so traditional image segmentation algorithms aimed at identifying specific subcellular components may not be reliable. We need to be clever to ferret […]

December 13, 2016. Postdoctoral Position available for high performance computing application in radiation biodosimetry

A postdoctoral position is available  to work on a newly funded high-performance computing project:  ​ “Automated Cytogenetic Dosimetry as a Public Health Emergency Medical Countermeasure.”  This 2 year project is supported by the  SOSCIP-TalentEdge program. ​Candidates should be qualified in C++ development, preferably with experience in parallel computing. The position is at Western University in combination with the […]

December 6, 2016. Finding mutations in transcription factor binding sites with MutationForecaster

Genome-scale transcription factor binding site analysis now available on MutationForecaster: Cytognomix‘s goal is to enable complete gene or genome bioinformatic mutation interpretation for our customers and partners. We will be introducing multiple new types of mutation analyses to our MutationForecaster ® product over the coming year. We are excited to announce the first of these […]

December 1, 2016. Faux controversies in variant genomic analysis

Recently, we published 2 papers describing our unifying framework for non-coding mutation analysis (Mucaki et al. BMC Medical Genomic, 2016;, and Caminsky et al. Human Mutation, 2016;  Among the results were SNP analyses of transcription factor binding site mutations. These gene regions are very rich in variation, but only a small percentage of […]

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