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.
Run 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)
Subscribe and analyze your own data via the cloud or… Don’t want to run your own analyses on MutationForecaster®? Let us do it for you with our Bespoke Analysis Service.
Experience our suite of genome interpretation products through a free trial of MutationForecaster®. Once you register, we provide datasets from our peer-reviewed publications to evaluate these software tools.
Automated radiation biodosimetry
Ionizing radiation produces characteristic chromosome changes. The altered chromosomes are known as dicentric chromosomes [DCs]). DC biodosimetry is approved by the IAEA for occupational radiation exposure, radiation emergencies, or monitoring long term exposures. The DC assay can also monitor effects of interventional radiation therapies.
Cytognomix has developed a novel approach to find DCs (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 to 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 metaphase scanning systems, selects high quality cells, identifies dicentric chromosomes, 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 and gene signatures that others cannot with advanced, patented genomic bioinformatic technologies. Cytognomix continues our long track record of creating technologies for genomic medicine. We anticipate and implement the needs of the molecular medicine and genomics communities.
Predict chemotherapy outcomes
Pharmacogenomic responses to chemotherapy drugs can be predicted by supervised machine learning of expression and copy number of relevant gene combinations. Since 2015, CytoGnomix has used biochemical evidence to derive gene signatures from changes in gene expression in cell lines, which can subsequently be examined in patients that have been treated with the same drugs. We have derived signatures for 30 different commonly used drugs. Try out out our online predictor: https://chemotherapy.cytognomix.com.
Quantifying responses to ionizing radiation with gene expression signatures.
Gene signatures derived by machine learning have low error rates in externally validated, independent radiation exposed data. They exhibit high specificity and granularity for dose estimation in humans and mice. These signatures can be designed to avoid the effects of confounding, comorbidities which can reduce specificity for detecting radiation exposures. See: https://f1000research.com/articles/7-233/v2
Single copy genomic technologies
- Customized genomic microarrays
- Ultrahigh resolution FISH probes (article):
- 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