Tag Archives: interpretation of SNPs

Sept. 7, 2019. Pan cancer article and database update

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We have published another revision to our pan-cancer splicing mutation database  paper: Shirley BC, Mucaki EJ and Rogan PK. Pan-cancer repository of validated natural and cryptic mRNA splicing mutations F1000Research 2019, 7:1908 (https://f1000research.com/articles/7-1908/v3). The paper is already indexed in PubMed.
In this version, we derive a simplified variant classification scheme with  ClinVar designations calibrated to the molecular phenotypes of mRNA splicing mutations. These are now indicated in the ValidspliceMut (https://validsplicemut.cytognomix.com) query results. The majority of variants cause aberrant splicing or are likely aberrant. Interestingly, a significant fraction of variants that have the same information, expression, population frequency properties as ClinVar variants designated as “benign” cause allele-specific alternative splicing.

Figure 1 of Pan-cancer repository of validated natural and cryptic mRNA splicing mutations. F1000Research 2019, 7:1908

March 20, 2019. Presentation at the 2019 American College of Medical Genetics and Genomics annual conference

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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 will be available as an ePoster AS WELL AS being presented in printed format on a poster board during the Annual Meeting.  Details to access the ePoster will be available soon.

 

 

 

 

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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 Cyto Visualization Analytics.  With Workflows,  automatically perform end-to-end analysis with all of our software products. 

Download an 1 page overview of MutationForecaster®: link .

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Resources

Links to the latest CytoGnomix products:

Applications and consulting in Geostatistical Epidemiology

Monitoring and discriminating infectious disease hotspots from high disease burden regions, eg. for COVID-19:

Zenodo repository:  Geostatistical Analysis of SARS-CoV-2 Positive Cases in the United States

Defence Canada IDEaS project: Locating emerging COVID19 hotspots in Ontario after community transmission by time-correlated, geospatial analysis 

Addressing large scale radiation incidents and accidents: 

Article in PLOS One: Meeting radiation dosimetry capacity requirements of population-scale exposures …. (Funded by High performance computing consortium: SOSCIP and CytoGnomix)

How to: Protocol for Geostatistical Determination of Radiation Dosimetry Maps of Population-Scale Exposures 

Large scale Radiation Biodosimetry

Capacity of supercomputer version of Automated Dicentric Chromosome Identifier and Dose Estimator  (ADCI) software: Automated Cytogenetic Biodosimetry at Population-Scale and Radiation, Radiation, 2021 (link to published article).

Scalable, democratized access to ADCI:

Overview of Cloud version- ADCI_Online

Presentation to the International Atomic Energy Agency (CRP E35010)

Gene Expression Signatures for Radiation Biodosimetry

Mucaki, E.J., Shirley, B.C. and Rogan, P.K., 2021. Improved radiation expression profiling in blood by sequential application of sensitive and specific gene signatures. International Journal of Radiation Biology,   doi.org/10.1080/09553002.2021.1998709    Link to pdf: Improved radiation expression profiling…

Zhao, J.Z., Mucaki, E.J. and Rogan, P.K., 2018. Predicting ionizing radiation exposure using biochemically-inspired genomic machine learning. F1000Research, 7(233), p.233.   Link to open access article: https://f1000research.com/articles/7-233

Large Scale Repository of Cancer Splicing Mutations

Pan-cancer repository of validated natural and cryptic mRNA splicing mutations   (a major public resource of mRNA splicing mutations validated according to multiple lines of evidence of abnormal gene expression. )

Article in F1000Research: Pan-Cancer repository of …..

Presentation at the 2019 American College of Medical Genetics Annual Meeting:

Pan-cancer repository of validated natural and cryptic mRNA.ePoster

Interactive Website: Gene signatures for chemotherapy drug response

Demo (Windows): Automated Dicentric Chromosome Identifier and Dose Estimator  

Review on information theory-based splicing mutation analysis:

Caminsky et al. 2014, Videos describing this paper: short and long versions.

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