Yearb Med Inform 2014; 23(01): 212-214
DOI: 10.15265/IY-2014-0039
Original Article
Georg Thieme Verlag KG Stuttgart

Managing Large-Scale Genomic Datasets and Translation into Clinical Practice

T. Lecroq
1   Normandie Univ., University of Rouen, NormaSTIC FR CNRS 3638, IRIB and LITIS EA 4108, Information Processing in Biology & Health, Mont-Saint-Aignan, France
,
L. F. Soualmia
1   Normandie Univ., University of Rouen, NormaSTIC FR CNRS 3638, IRIB and LITIS EA 4108, Information Processing in Biology & Health, Mont-Saint-Aignan, France
,
Section Editors for the IMIA Yearbook Section on Bioinformatics and Translational Informatics › Author Affiliations
Further Information

Publication History

15 August 2014

Publication Date:
05 March 2018 (online)

Summary

Objective:To summarize excellent current research in the field of Bioinformatics and Translational Informatics with application in the health domain.

Method: We provide a synopsis of the articles selected for the IMIA Yearbook 2014, from which we attempt to derive a synthetic overview of current and future activities in the field. A first step of selection was performed by querying MEDLINE with a list of MeSH descriptors completed by a list of terms adapted to the section. Each section editor evaluated independently the set of 1,851 articles and 15 articles were retained for peer-review.

Results: The selection and evaluation process of this Yearbook’s section on Bioinformatics and Translational Informatics yielded three excellent articles regarding data management and genome medicine. In the first article, the authors present VEST (Variant Effect Scoring Tool) which is a supervised machine learning tool for prioritizing variants found in exome sequencing projects that are more likely involved in human Mendelian diseases. In the second article, the authors show how to infer surnames of male individuals by crossing anonymous publicly available genomic data from the Y chromosome and public genealogy data banks. The third article presents a statistical framework called iCluster+ that can perform pattern discovery in integrated cancer genomic data. This framework was able to determine different tumor subtypes in colon cancer.

Conclusions: The current research activities still attest the continuous convergence of Bioinformatics and Medical Informatics, with a focus this year on large-scale biological, genomic, and Electronic Health Records data. Indeed, there is a need for powerful tools for managing and interpreting complex data, but also a need for user-friendly tools developed for the clinicians in their daily practice. All the recent research and development efforts are contributing to the challenge of impacting clinically the results and even going towards a personalized medicine in the near future.

 
  • References

  • 1 Lecroq T, Soualmia LF. From genome sequencing to bedside. Findings from the section on bioinformatics and translational informatics.. Yearb Med Inform 2013; 8 (01) 175-7.
  • 2 Kohane IS, Churchill SE, Murphy SN. A translational engine at the national scale: informatics for integrating biology and the bedside.. J Am Med Inform Assoc 2012; Mar-Apr 19 (02) 181-5.
  • 3 Tian Q, Prics ND, Hood L. Systems cancer medicine: towards realization of predictive, preventive, personalized and participatory (P4) medicine.. J Intern Med 2012; Feb 271 (02) 111-21.
  • 4 Pelak K, Shianna KV, Ge D, Maia JM, Zhu M, Smith JP. et al. The characterization of twenty sequenced human genomes.. PLoS Genet 2010 Sep 9;6(9) e1001111.
  • 5 1000 Genomes Project Consortium,. Abecasis GR, Auton A, Brooks LD, DePristo MA, Durbin RM, Handsaker RE. et al. An integrated map of genetic variation from 1,092 human genomes.. Nature 2012; Nov 1 491 7422 56-65.
  • 6 Starren J, Williams MS, Bottinger EP. Crossing the omic chasm: a time for omic ancillary systems.. JAMA 2013; Mar 27 309 (12) 1237-8.
  • 7 Stubbs A, McClellan EA, Horsman S, Hiltemann SD, Palli I, Nouwens S. et al. Huvariome: a web server resource of whole genome next-generation sequencing allelic frequencies to aid in pathological candidate gene selection.. J Clin Bioinform 2012; Nov 19 2 (01) 19.
  • 8 Samur MK, Yan Z, Wang X, Cao Q, Munshi NC, Li C. et al. canEvolve: a web portal for integrative oncogenomics.. PLoS One 2013; 8 (02) e56228.
  • 9 Gonzalez MA, Lebrigio RF, Van Booven D, Ulloa RH, Powell E, Speziani F. et al. GEnomes Management Application (GEM.app): a new software tool for large-scale collaborative genome analysis.. Hum Mutat 2013; Jun 34 (06) 842-6.
  • 10 Cao DS, Liang YZ, Deng Z, Hu QN, He M, Xu QS, Zhou GH. et al. Genome-scale screening of drug-target associations relevant to Ki using a chemogenomics approach.. PLoS One 2013; 8 (04) e57680.
  • 11 Carter H, Douville C, Stenson PD, Cooper DN, Karchin R. Identifying Mendelian disease genes with the Variant Effect Scoring Tool.. BMC Genomics 2013; 14 Suppl (03) S3.
  • 12 Farley T, Kiefer J, Lee P, Von Hoff D, Trent JM, Colbourn C. et al. The BioIntelligence Framework: a new computational platform for biomedical knowledge computing.. J Am Med Inform Assoc 2013; Jan 1 20 (01) 128-33.
  • 13 Pokorny J. NoSQL databases: a step to database scalability in web environment.. International Journal of Web Information Systems 2013; 9 (01) 69-82.
  • 14 Kodama Y, Shumway M, Leinonen R. International Nucleotide Sequence Database Collaboration. The Sequence Read Archive: explosive growth of sequencing data.. Nucleic Acids Res 2012; Jan 40 (-Database issue) D54-6.
  • 15 Gymrec M, McGuire AL, Golan D, Halperin E, Erlich Y. Identifying personal genomes by surname inference.. Science 2013; Jan 18 339: 321-4.
  • 16 Korf BR, Rehm HL. New approaches to molecular diagnosis.. JAMA 2013; Apr 10 309 (14) 1511-21.
  • 17 Lamy JB. BibReview.. http://extranet-limbio.smbh.univ-paris13.fr/html/limbio/claroline/backends/download.