Winners Announced for the 2017 DCEG Informatics Tool Challenge
, by DCEG Staff
Five winners of the 2017 DCEG Informatics Tool Challenge were announced in May. Since 2014, this competitive funding program has provided support for innovative approaches to enhance epidemiological methods, data collection, analysis, and other research efforts of the Division through the use of modern technology and informatics.
Proposals are evaluated for their novel approach to specific research needs, ability for the project to be completed within one year of initiation, and cost, which cannot exceed $20,000. Reviewers considered the utility to epidemiologic and genetic research as well as technical feasibility.
Several of the winners this year are extending projects initiated with earlier awards from the Informatics Tool Challenge program. The NCI Center for Biomedical Informatics and Information Technology (CBIIT) is providing technical support for three of the projects, collaborators on other projects include the NCI Division of Cancer Control and Population Sciences (DCCPS), the NIH Center for Information Technology (CIT), Westat, and George Washington University and The Ohio State University.
Out of nine submitted proposals, the five described below were selected for funding.
SOCcer in the field: Subject coding of own occupational history during interview with assistance from the SOCcer automated coding algorithm
Melissa Friesen, Gabriella Andreotti, Laura Beane Freeman (DCEG); Daniel Russ, Calvin Johnson (NIH/CIT)
In an extension of the previously developed SOCcer (Standardized Occupation Coding for Computer-assisted Epidemiologic Research) algorithm—which automates the assignment of SOCs to job descriptions from epidemiologic surveys—investigators will develop a new approach to further reduce the need for expert review in cases where the top ranked code has a low SOCcer score, or where the top two ranked codes have very similar scores. “SOCcer in the field” will allow study participants to code their own job descriptions in a web-based questionnaire. This approach will be piloted in the new Early Life Exposures in Agriculture Study.
Biological sampling, processing and storage cost estimation tool
Annelie Landgren, Hannah Yang, Amanda Black, Stephanie Weinstein (DCEG)
This user-friendly tool will help researchers easily and accurately estimate costs for epidemiologic studies that involve collecting and storing biologic specimens. Users will be able to input information on their specific studies and calculated cost based on a customizable, periodically-updated list of estimates for supplies, storage, shipping, etc.
Web-based computer program for organ dose estimations for patients undergoing computed tomography
Choonsik Lee (DCEG)
The existing National Cancer Institute dosimetry system for Computed Tomography (NCICT) to estimate radiation dose to a patient’s organs during a CT procedure can only be utilized by users with a Windows operating system. Dr. Lee will lead translation of the tool to a web-based program, thereby allowing its use by a wider set of clinical researchers and collaborators, as well as by more physicists and radiologists at hospitals. The new format will also be accessible on mobile devices.
LDlink feature expansion and maintenance
Mitchell Machiela (DCEG)
Released in June 2015, LDlink is a publicly accessible web-based bioinformatic tool that helps genetic researchers explore regional linkage disequilibrium (LD) and link correlated alleles for functional studies. This enhancement of LDlink is a result of requests by the growing user base. Additional features will include expanded user control of inputs and outputs, and improvement of visualization and error messages. Minor user-reported bugs will also be fixed.
Expansion of COMETS-Analytics: A data analysis platform for multi-cohort metabolomics analyses
Steven Moore, Joshua Sampson (DCEG); Krista Zanetti (DCCPS); Sue Pan (CBIIT); Ella Temprosa (George Washington University); Ewy Mathé (The Ohio State University)
This project focuses on adding additional statistical capabilities to the Consortium of Metabolomics Studies (COMETS) online application, COMETS-Analytics. The initial app was developed last year to analyze data from 36 international prospective cohorts and cohort consortia using metabolomics in studies of disease etiology. To broaden the scope of possible analyses, researchers will add the capacity to perform logistic regression and proportional hazards regression to complement the existing correlational analysis function.