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.
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- 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.
We have added the capability to determine whether samples exposed to ionizing radiation are wholly or partially irradiated. If partially, the approach determines the fraction of metaphase cells exposed and the whole body-equivalent dose completely automatically. CytoGnomix’s Automated Dicentric Chromosome Identifier and Dose Estimation software has been upgraded to generate these results as part of […]
We are giving a platform presentation at the upcoming American Society of Human Genetics virtual meeting #ASHG2020 Session: Personalized Medicine Approaches in Healthcare. Paper: Pathway-extended gene expression signatures integrate novel biomarkers that improve predictions of responses to kinase inhibitors P. K. Rogan(1,2), A. J. Bagchee-Clark(1), E. J. Mucaki(1). 1. Department of Biochemistry, University of Western […]
Peter Rogan was interviewed by Gill Eapin for his daily podcast, Scientific Sense, focused on Science & Economics about our research projects about COVID19. Listen at the link below. https://anchor.fm/scientificsense/episodes/Prof–Peter-Rogan–Professor-of-Biochemistry-and-Biostatistics-at-Western-University-ei5i40 #medicine #sarscov2 #covidー19 #medicalsciences #epidemiology #health #geostatistics #hotspots #publichealth #genomics #molecularmechanism
We have described and provide evidence for an explanation for how rapid onset, severe RNA viral infections, such as SARS-CoV-2 or Influenza, may develop: Rogan PK, Mucaki EJ and Shirley BC. A proposed molecular mechanism for pathogenesis of severe RNA-viral pulmonary infections. F1000Research 2020, 9:943 (https://doi.org/10.12688/f1000research.25390.1) There is an accompanying infographic describing the mechanism, which is cited in […]
We have just published a new version (#4) of our archive containing geostatistical analyses of SARS-CoV-2 positive cases in the United States (https://doi.org/10.5281/zenodo.3890284). This version adds state-by-state results after Federal and State relaxation of distancing constraints on Memorial Day weekend using space-time, countywide geostatistical analysis.
Version 3 of Geostatistical Analysis of SARS-CoV-2 in the United States dataset published (http://doi.org/10.5281/zenodo.3950057). Contains hotspot and cluster analysis of daily case counts across all US counties from Marcy 25-July 13, 2020. #covid-19 #SARSCov2 #geostatistics #hotspot
CytoGnomix has coauthored a new article on collaborative gene variant interpretation applied to selection of cancer therapy: Shruti Rao, Beth Pitel, Alex H Wagner, Simina M Boca, Matthew McCoy, Ian King, Samir Gupta, Ben Ho Park, Jeremy L Warner, James Chen, Peter K Rogan, Debyani Chakravarty, Malachi Griffith, Obi L Griffith, Subha Madhava. Collaborative, Multidisciplinary Evaluation of Cancer Variants Through Virtual Molecular Tumor Boards Informs Local Clinical Practices. DOI: […]