MutationForecaster® (mutationforecaster.com) 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.
Browse the products section of the menu found in the header bar for more information regarding any of our services.
- Don’t want to run your own analyses on MutationForecaster®? Let us do it for you with our Bespoke Analysis Service.
- Customized genomic microarrays
- Ultrahigh resolution FISH probes:
- Microarray-based comparative genomic hybridization (aCGH) can use SC technology to increase reproducibility and reduce cost per sample.
Aug. 13, 2018. Differential accessibility to homologous chromosomal loci confirmed by international consortium
A large international consortium based at Harvard University has demonstrated parental homolog-specific differences in chromatin accessibility on human chromosome 19: Nir et al. BioRxiv doi: 10.1101/374058 (Walking along chromosomes with super-resolution imaging, contact maps, and integrative modeling) This work reproduces previous reports previously published by CytoGnomix scientists using our patented scFISH™ probes: Khan et al. Molecular […]
The 2018 Impact report from the Southern Ontario Smart Computing for Innovation Platform (SOSCIP), which supports the development of a supercomputer version of the Automated Dicentric Chromosome and Dose Estimation (ADCI) system in IBM Blue Gene/Q, contains an article about our project: […]
Population scale biodosimetry with the Automated Dicentric Chromosome Identifier and Dose Estimator (ADCI) software system. (Platform) Rogan PK, Ali, S, Li Y, Shirley B, Wilkins R, Flegal F, Cooke R, Peerlaproulx T, Waller E, Knoll JHM. EPR Biodose 2018, June 11-15, Munich Germany Optimization of image selection in Automated Dicentric Chromosome Analysis. […]
As of today, we have transitioned the website cytognomix.org to: http://academic.cytognomix.com The site contains our published articles, lectures and presentations about human genetics and molecular biology. All of the legacy content at this site (1980-2007) will be preserved on the new site. Please update your browser bookmarks to reflect this change.
CytoGnomix’s Mutation Forecaster: Key to discovery of mutations in novel ALS gene. Nicolas et al. Genome-wide Analyses Identify KIF5A as a Novel ALS Gene. Neuron 97:1268-1283.e6, 2018 http://www.cell.com/neuron/fulltext/S0896-6273(18)30148-X From our subscriber, Dr. John Landers (U. Mass. School of Medicine): “We used the application ASSEDA (Automated Splice Site and Exon Definition Analyses) to predict any mutant […]
April 9, 2018. Upcoming release of Automated Dicentric Chromosome Identifier and Dose Estimator (ADCI)
We have just completed porting Windows ADCI from the MinGW C++ (32 bit) to Microsoft’s C++ (64 bit) compiled version. The release of this software in summer 2018 will contain this new version (v 2.0). ADCI now has access to 8 Gb of runtime memory, which should allow twice as many samples to be batch […]
Clustered, information-dense transcription factor binding sites identify genes with similar tissue-wide expression profiles. BioRxiv, 2018. doi: https://doi.org/10.1101/283267