Genome-Scale Variant Interpretation
Automated Radiation Dose Estimation
Mission Statement
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.
Latest Posts
March 9, 2014. Commentary on Mutation interpretation: current limitations and approaches to overcome them
Why do we sequence gene panels, exomes and complete genomes? To find mutations in genes, of course. This is the currency that allows bioinformaticists and clinicians to determine which metabolic pathways are dysregulated in patients with gene-based disease. What has surprised me most about NGS since the development of this wonderful technology for finding variation […]
March 7, 2014. Veridical software paper indexed for PubMed and highlighted on the RNA-Seq Blog
The article has been published for 7 weeks and has been downloaded or viewed 562 times. Three peer reviews have been submitted to date: one approved and two approved with reservations. We are addressing these comments now and modifying the manuscript accordingly. Viner C, Dorman SN, Shirley BC and Rogan PK (2014) Validation of predicted […]
March 3, 2014. Oral presentation at the The Fifth International Symposium on Hereditary Breast and Ovarian Cancer Conference
Our abstract, “Identification, Prediction and Prioritization of Non-Coding Variants of Uncertain Significance in Heritable Breast/Ovarian Cancer,” has been accepted for oral presentation at the BRCA: Twenty Years of Advances – The Fifth International Symposium on Hereditary Breast and Ovarian Cancer Conference in Montreal, Quebec (Apr 23-25). The authors are: E.J. Mucaki(1), N. Caminsky(1), A. Stuart(1), C. Viner(1), B. Shirley(2), […]
February 28, 2014. The Shannon splicing mutation software pipeline is online
The Shannon mutation pipeline is now available by online subscription. See our announcement !
February 6, 2014. Biodosimetry manuscript accepted for publication
The paper that we presented at the 2013 EPR BioDose meeting is now in press in the journal: Radiation Protection Biodosimetry: Automating dicentric chromosome detection from cytogenetic biodosimetry data Peter K. Rogan*1, Yanxin Li1, Asanka Wickramasinghe1, Akila Subasinghe1, Natasha Caminsky1, Wahab Khan1, Jagath Samarabandu1, Joan H. Knoll1, Ruth Wilkins2, and Farrah Flegal3 1University of Western […]
Jan. 29, 2014. Translational Breast Cancer Research Retreat in London, Ontario
Stephanie Dorman’s presentation of our analysis of Cancer Genome Atlas genomic and clinical data of somatic breast cancer on January 10, 2014 has been highlighted in the Breast Cancer Society of Canada blog: http://www.bcsc.ca/blog/2014/01/29/london-citywide-breast-cancer-retreat-2014/
Jan. 13, 2014. New paper and software for experimental evaluation of predicted mutations in genomes or exomes
We have just published a paper describing method and companion software for experimental validation of mutations with NGS (RNASeq) data: Validation of predicted mRNA splicing mutations using high-throughput transcriptome data. Coby Viner, Stephanie N. Dorman, Ben C. Shirley, Peter K. Rogan. published in F1000Research ( http://f1000research.com/articles/3-8/v1 ) This approach fills a critical unmet need in genome-scale […]
Jan. 10, 2014. Presentation at the The Fifth International Symposium on Hereditary Breast and Ovarian Cancer
Our abstract, “Identification, Prediction and Prioritization of Non-Coding Variants of Uncertain Significance in Heritable Breast/Ovarian Cancer,” has been accepted for presentation at the BRCA: Twenty Years of Advances – The Fifth International Symposium on Hereditary Breast and Ovarian Cancer Conference in Montreal, Quebec (Apr 23-25). The authors are: E.J. Mucaki(1), N. Caminsky(1), A. Stuart(1), C. Viner(1), […]
