Biology subjects

Warner, J.

Publications and source records attributed to Warner, J..

3 recordsLinked to original sources

bioRxiv2018

Longitudinal Visual Analytics for Unpacking the Cancer Journey

Retrospective cancer research requires identification of patients matching both categorical and temporal inclusion criteria, often based on factors exclusively available in clinical notes. Although natural language processing approaches for inferring higher-level concepts have shown promise for bringing structure to clinical texts, interpreting results is often challenging, involving the need to move between abstracted representations and constituent text elements. We discuss qualitative inquiry into user tasks and goals, data elements and models resulting in an innovative natural language processing pipeline and a visual analytics tool designed to facilitate interpretation of patient summaries and identification of cohorts for retrospective research.

cancer biology↗

bioRxiv2018

A harmonized meta-knowledgebase of clinical interpretations of cancer genomic variants

Precision oncology relies on the accurate discovery and interpretation of genomic variants to enable individualized diagnosis, prognosis, and therapy selection. We found that knowledgebases containing clinical interpretations of somatic cancer variants are highly disparate in interpretation content, structure, and supporting primary literature, impeding consensus when evaluating variants and their relevance in a clinical setting. With the cooperation of experts of the Global Alliance for Genomics and Health (GA4GH) and six prominent cancer variant knowledgebases, we developed a framework for aggregating and harmonizing variant interpretations to produce a meta-knowledgebase of 12,856 aggregate interpretations covering 3,437 unique variants in 415 genes, 357 diseases, and 791 drugs. We demonstrated large gains in overlap between resources across variants, diseases, and drugs as a result of this harmonization. We subsequently demonstrated improved matching between a patient cohort and harmonized interpretations of potential clinical significance, observing an increase from an average of 33% per individual knowledgebase to 56% in aggregate. Our analyses illuminate the need for open, interoperable sharing of variant interpretation data. We also provide an open and freely available web interface (search.cancervariants.org) for exploring the harmonized interpretations from these six knowledgebases.

bioinformatics↗

bioRxiv2018

NvERTx: A gene expression database to compare Embryogenesis and Regeneration in the sea anemone Nematostella vectensis

For more than a century researchers have been comparing embryogenesis and regeneration hoping that lessons learned from embryonic development will unlock hidden regenerative potential. This problem has historically been a difficult one to investigate since the best regenerative model systems are poor embryonic models and vice versa. Recently however, the comparison of embryogenesis and regeneration has seen renewed interest as emerging models including the sea anemone Nematostella vectensis have allowed researchers to investigate these processes in the same organism. This interest has been further fueled by the advent of high-throughput transcriptomic analyses that provide virtual mountains of data. Unfortunately much of this data remains in raw unanalyzed formats that are difficult to access or browse. Here we present Nematostella vectensis Embryogenesis and Regeneration Transcriptomics - NvERTx, the first platform for comparing gene expression during embryogenesis and regeneration. NvERTx is comprised of close to 50 RNAseq datasets spanning embryogenesis and regeneration in Nematostella. These data were used to perform a robust de novo transcriptome assembly which users can search, BLAST and plot expression of multiple genes during these two developmental processes. The site is also home to the results of gene clustering analyses, to further mine the data and identify groups of co-expressed genes. The site can be accessed at http://nvertx.kahikai.org.

developmental biology↗