September 7, 2015. Video presentation of Molecular Oncology article on chemotherapy response

We have published a video synopsis of :

Genomic signatures for paclitaxel and gemcitabine resistance in breast cancer derived by machine learning.  Stephanie N. Dorman, Katherina Baranova, Joan H.M. KnollBrad L. UrquhartGabriella MarianiMaria Luisa Carcangiu, Peter K. Rogan. Molecular Oncology, in press. DOI:

Aug. 25, 2015. Top viewed article in Molecular Cytogenetics

Our article:

Reversing chromatin accessibility differences that distinguish homologous mitotic metaphase chromosomesWahab Khan, Peter Rogan, Joan Knoll. Molecular Cytogenetics 2015, 8:65

was published on August 13th. In less than two weeks, it has become the most viewed article in this journal for the past month, averaging 55 per day.

Update: as of Sept. 6, the article is still the top viewed paper with 887 views.


August 13, 2015. New paper on metaphase epigenetics published

The next exciting installment of the “story” about differential accessibility of metaphase chromosomes has been published.  Cytognomix’s single copy FISH technology was key to making these observations. 
Reversing chromatin accessibility differences that distinguish homologous mitotic metaphase chromosomes.  Khan et. al. Molecular Cytogenetics 2015, 8:65 

July 31, 2015. Chemotherapy resistance in breast cancer manuscript accepted for publication

Genomic signatures for paclitaxel and gemcitabine resistance in breast cancer derived by machine learning

Authors:  Stephanie N. Dormana, Katherina Baranovaa, Joan H.M. Knollb,c,d, Brad L. Urquharte, Gabriella Marianif, Maria Luisa Carcangiuf, Peter K. Rogana,d,g,h*

aDepartment of Biochemistry, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada, bDepartment of Pathology and Laboratory Medicine, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada, cMolecular Diagnostics Division, Laboratory Medicine Program, London Health Sciences Centre, ON, Canada, dCytognomix Inc., London ON, Canada, eDepartment of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada, fDepartment of Diagnostic and Laboratory Pathology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy, gDepartment of Computer Science, University of Western Ontario, London, ON, Canada, hDepartment of Oncology, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada

will be published in a forthcoming issue of the journal “Molecular Oncology”.

July 3, 2015. New publication on breast cancer gene mutation

FANCM c.5791C>T nonsense mutation (rs144567652) induces exon skipping, affects DNA repair activity, and is a familial breast cancer risk factor.
Peterlongo et al. Hum Mol Genet. 2015 Jun 30. pii: ddv251.

In this paper, we use information theory to demonstrate a new mechanism for disease mutations. It turns out that this a fairly common type of mutation in our unpublished studies of other data sources.


June 27, 2015. Best oral presentation at the 12th Annual London Oncology Research & Education Conference

Natasha Caminsky presented:

A Unified Framework for the Identification and Prioritization of Coding and Non-Coding Variants in Heritable Breast and Ovarian Cancer (HBOC).

which introduces Cytognomix’s approach for analysis of a wide range of regulatory mutations in complete human gene and genome data. The other authors of this study were  Mucaki EJ, Lu R, Perri AM, and Rogan PK.

This is an annual event for scientists, clinicians, graduate students and Post-Doctoral fellows at the University of Western Ontario and affiliated hospitals to share cancer research discoveries and promote cancer research collaboration and training.   She was awarded Best Oral Presentation for this paper.

The Breast Cancer Society of Canada blogged the results of the paper competition: link

April 18, 2015. New software distribution agreement for MutationForecaster

Today, Cytognomix Inc. and Illumina  signed a distribution agreement to make MutationForecaster software available through the BaseSpace ecosystem. Work is underway to enable Illumina users to analyze data processed in BaseSpace to be interpreted with Cytognomix’s software.  The BaseSpace environment enables MiSeq users to carry out sequence analyses with requiring an  onsite computing infrastructure, with scalable cloud data storage, to manage all of your data analyses, to securely collaborate, and to share and access Illumina and community-developed applications. MutationForecaster will import variant control format files, validate them with RNASeq Bam files from the same sample directly from BaseSpace  and download results from Cytognomix back to BaseSpace.

May 21, 2015. Platform presentation at Compute Ontario Research Day

Dr. Peter Rogan’s laboratory at the University of Western Ontario will present:

 Discovery of Primary, Cofactor, and Novel Transcription Factor Binding Site Motifs by Recursive, Thresholded Entropy Minimization

by Ruipeng Lu 1, Eliseos Mucaki 2, and Peter Rogan 1,2,3.    Departments of (1) Computer Science and (2)Biochemistry, University of Western Ontario, and (3)Cytognomix Inc., London ON

at Compute Ontario (abstract), Conestoga College, Cambridge Ontario, Canada. The presentation is in Room A2107 at 13:55 at the Conestoga College Institute of Technology and Advanced Learning.

April 30. Sale of MutationForecaster subscription

Cytognomix has sold an annual subscription to MutationForecaster, our comprehensive solution for next generation sequencing based mutation interpretation, to a hospital in Toronto, Ontario Canada. This customer was a previous subscriber to the Automated Site and Exon Definition Server, which is embedded in MutationForecaster and no longer available as standalone software.

March 11, 2015. Invited presentation at the University of Ontario Institute of Technology

SHARCNET Scientific Computing Seminar Series

Wednesday 11 March, 11am-12pm, ERC 1056

Peter K. Rogan, CRC (Tier I) in Genome Bioinformatics, Department of Biochemistry & Department of Computer Science, University of Western Ontario, and

Cytognomix Inc, London ON

Mutation Forecaster, a software resource for genome-scale analysis of complete genes and human genomes

Complete genome sequencing is now feasible, becoming cost effective, and increasingly an essential component of cancer discovery and patient genomic analyses. This has created a bottleneck in interpretation of gene variants, partly because the effects of most variants remain unknown (variants of unknown significance, VUS), and also because interpretation is confounded by the lack of corresponding genetic information from closely related family members.   The VUS problem is now exacerbated by the discovery of massive numbers of variants in each genome, many never before seen. Technologies that prune variants in an individual are essential to perform any large scale gene panel, exome or genome analysis.  The variant analysis approaches I will describe improves complete gene and genome sequence analyses and by detecting dysregulated biochemical pathways.  We stratify variants by mutation severity, which can suggesting or exclude particular therapeutic options (Shirley et al. 2013 <>; Dorman et al. 2014 <>; Mucaki et al. 2011 <>; Mucaki et al. 2013 <>, Viner et al. 2014 <>).Our patented software computes changes in information content in DNA or RNA sequences. These changes tell us which sequences disrupt the regulation of genes and how severe these changes are.   Our methods have been validated in hundreds of published studies (Caminsky et al. 2014 <>), and use proven information theory, one of the most important scientific advances of the last century. I will introduce a single system that amalgamates several of our software products, and which also queries existing public databases and store results for users. MutationForecaster <> provides basic capabilities offered by others, but also offers proven mutation interpretation  methods not available elsewhere. This leads to more comprehensive mutation results and ultimately, a more complete understanding of the dysregulation of disease genomes.