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.
We’re giving a demonstration and a poster presentation of our new GA4GH-compliant web-based Beacon (https://validsplicemut.cytognomix.com) at the 2019 American College of Medical Genetics and Genomics annual conference this week. Here are the details: Pan-Cancer Repository of Validated Natural and Cryptic mRNA Splicing MutationsCategory: “Laboratory genetics and genomics”, Abstract Poster Number: 754 (link to abstract) Where: Exhibit hall, Washington […]
March 20, 2019. Presentation at the 2019 American College of Medical Genetics and Genomics annual conference
The following paper has been accepted for presentation: “Pan-Cancer Repository of Validated Natural and Cryptic mRNA Splicing Mutations”, Category: “Laboratory genetics and genomics”, Abstract Poster Number: 754 (link to Abstract) Where: Exhibit hall, Washington Convention Center, ACMG Clinical Genetics Meeting in Seattle, Washington When: April 2 – 6, 2019; Poster presentation time: Friday, 4/5 from 10:30am-12:00pm This work […]
New article in bioRxiv: Expression changes confirm predicted single nucleotide variants affecting mRNA splicing. E. J. Mucaki and P.K. Rogan. (https://www.biorxiv.org/content/10.1101/549089v1) This paper describes high quality qRT-PCR and microarray expression data of predicted splicing variants. The results confirm results of genome-wide TCGA and ICGC RNASeq findings (https://f1000research.com/articles/7-1908/v1). The genome scale results were obtained using CytoGnomix’s […]
CytoGnomix is licensing its Automated Dicentric Chromosome Identifier and Dose Estimator product to a Canadian government-owned contractor-operated laboratory through 2020. This organization’s primary business is in nuclear science and technology.
We have just updated the CytoVA software product. It now contains all PubMed references through Dec 2018 and the most recent version of the human phenotype ontology (HPO). With CytoVA (see below), you can query Shannon pipeline, Veridical or VEP output, the list of predicted deleterious variants, with this software for HPO clinical phenotypes. The […]
January 9, 2019. Article on fully automated interpretation of the dicentric chromosome assay for radiation quantification now available
Our paper, “RADIATION DOSE ESTIMATION BY COMPLETELY AUTOMATED INTERPRETATION OF THE DICENTRIC CHROMOSOME ASSAY” is now published in the journal Radiation Protection Dosimetry. Unfortunately, the journal has not made the article open access. We have made it available on our ADCIWiki website, as permitted by the copyright agreement. The link to the pdf full text […]
Our paper: “Predicting responses to platin chemotherapy agents with biochemically-inspired machine learning” has been pulbished in the journal Signal Transduction and Targeted Therapy. The article is open access. Here is a link to the paper: https://rdcu.be/bgaGR
December 14. New paper published about regulation of gene transcription by information theory and machine learning
Lu R and Rogan PK. Transcription factor binding site clusters identify target genes with similar tissue-wide expression and buffer against mutations [version 1 ]. F1000Research 2018, 7:1933 (DOI: 10.12688/f1000research.17363.1): https://f1000research.com/articles/7-1933/v1