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Cancer Informatics

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Extending Information Retrieval Methods to Personalized Genomic-Based Studies of Disease

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Publication Date: 10 Feb 2015

Type: Review

Journal: Cancer Informatics

Citation: Cancer Informatics 2014:Suppl. 7 85-95

doi: 10.4137/CIN.S16354

Abstract

Genomic-based studies of disease now involve diverse types of data collected on large groups of patients. A major challenge facing statistical scientists is how best to combine the data, extract important features, and comprehensively characterize the ways in which they affect an individual’s disease course and likelihood of response to treatment. We have developed a survival-supervised latent Dirichlet allocation (survLDA) modeling framework to address these challenges. Latent Dirichlet allocation (LDA) models have proven extremely effective at identifying themes common across large collections of text, but applications to genomics have been limited. Our framework extends LDA to the genome by considering each patient as a “document” with “text” detailing his/her clinical events and genomic state. We then further extend the framework to allow for supervision by a time-to-event response. The model enables the efficient identification of collections of clinical and genomic features that co-occur within patient subgroups, and then characterizes each patient by those features. An application of survLDA to The Cancer Genome Atlas ovarian project identifies informative patient subgroups showing differential response to treatment, and validation in an independent cohort demonstrates the potential for patient-specific inference.


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What Your Colleagues Say About Cancer Informatics
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Compared with other journals we considered for publishing, Cancer Informatics provided extremely rapid but quality turnaround from draft submission to a flawlessly typeset final publication.  Moreover, sharing the article is now as easy as sharing a link with no subscriptions required, and additional code and data files are equally accessible, supporting reproducible research.  Because it has published many of our references we feel confident that our target readership must follow the journal.  This is further ...
Dr Seppo Karrila (Prince of Songkla University, Thailand)
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