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.
Cytognomix is exhibiting at the Ontario Centers of Excellence Annual Discovery Conference at the Toronto Convention Center. Ben Shirley will be representing the company and demonstrating some of our software products. We can be found at Booth 1711 (South Building 800 Level) in the High Performance Computing Pavilion on the main exhibit floor. We invite […]
Our abstract is being presented at The Cancer Genome Atlas’ 3rd Annual Scientific Symposium, at the Natcher Conference Center on the NIH Campus, Bethesda, MD. The presentation is: Non-coding mutation analysis reveals previously unrecognized pathways in lymph node-invasive breast cancer. Dorman, S.N.1, Viner, C.2, Rogan, P.K1,2,3. 1Department of Biochemistry and 2Department of Computer Science, University […]
Dr. Peter Rogan will be presenting a paper at the TCGA symposium at the Natcher Conference Center on the NIH Campus, Bethesda, MD on May 12-13, 2014. The title and authors are: Non-coding mutation analysis reveals previously unrecognized pathways in lymph node-invasive breast cancer. Dorman, S.N.1, Viner, C.2, Rogan, P.K1,2,3. 1Department of Biochemistry and 2Department of Computer Science, […]
Paper describing automated validation of splicing mutations using RNASeq data has been indexed in PubMed: Validation of predicted mRNA splicing mutations using high-throughput transcriptome data. Viner C, Dorman SN, Shirley BC, Rogan PK. Version 2. F1000Res. 2014 Jan 13 [revised 2014 Apr 7];3:8. doi: 10.12688/f1000research.3-8.v2. eCollection 2014. PMID: 24741438
We have published an article in Radiation Protection Biodosimetry describing our patented Automated Dicentric Chromosome Identifier Software for both Desktop and Supercomputer systems. The citation is: Peter K. Rogan, Yanxin Li, Asanka Wickramasinghe, Akila Subasinghe, Natasha Caminsky, Wahab Khan, Jagath Samarabandu, Ruth Wilkins, Farrah Flegal, and Joan H. Knoll. AUTOMATING DICENTRIC CHROMOSOME DETECTION FROM CYTOGENETIC BIODOSIMETRY DATA. Radiat Prot […]
Stephanie Dorman presented our paper, “Non-coding mutation analysis reveals previously unrecognized pathways in lymph node-invasive breast cancer,” (Abstract) at the Annual AACR meeting. The poster presentation was very well attended with more than 30 visitors, including representatives from several personalized medicine and genomics companies. Many of the attendees expressed interest in the Shannon human mRNA splicing mutation and Veridical […]
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 […]
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 […]