Literature DB >> 31337654

Value of Collaboration among Multi-Domain Experts in Analysis of High-Throughput Genomics Data.

Daoud Meerzaman1, Barbara K Dunn2.   

Abstract

The recent explosion and ease of access to large-scale genomics data is intriguing. However, serious obstacles exist to the optimal management of the entire spectrum from data production in the laboratory through bioinformatic analysis to statistical evaluation and ultimately clinical interpretation. Beyond the multitude of technical issues, what stands out the most is the absence of adequate communication among the specialists in these domains. Successful interdisciplinary collaborations along the genomics pipeline extending from laboratory experiments to bioinformatic analyses to clinical application are notable in large scale, well managed projects such as The Cancer Genome Atlas. However, in certain settings in which the various experts perform their specialized research activities in isolation, the siloed approach to their research contributes to the generation of questionable genomic interpretations. Such situations are particularly concerning when the ultimate endpoint involves genetic/genomic interpretations that are intended for clinical applications. In spite of the fact that clinicians express interest in gaining a better understanding of clinical genomic applications, the lack of communication from upstream experts leaves them with a serious level of discomfort in applying such genomic knowledge to patient care. This discomfort is especially evident among healthcare providers who are not trained as geneticists, in particular primary care physicians. We offer some initiatives that have potential to address this problem, with emphasis on improved and ongoing communication among all the experts in these fields, constituting a comprehensive genomic "pipeline" from laboratory to patient. ©2019 American Association for Cancer Research.

Entities:  

Mesh:

Year:  2019        PMID: 31337654      PMCID: PMC6801074          DOI: 10.1158/0008-5472.CAN-19-0769

Source DB:  PubMed          Journal:  Cancer Res        ISSN: 0008-5472            Impact factor:   12.701


  22 in total

Review 1.  Genomewide association studies and assessment of the risk of disease.

Authors:  Teri A Manolio
Journal:  N Engl J Med       Date:  2010-07-08       Impact factor: 91.245

Review 2.  Opportunities and Challenges in Genomic Sequencing for Precision Cancer Care.

Authors:  Michael L Cheng; David B Solit
Journal:  Ann Intern Med       Date:  2018-01-09       Impact factor: 25.391

3.  Communication and data-intensive science in the beginning of the 21st century.

Authors:  Jack Faris; Evelyne Kolker; Alex Szalay; Leon Bradlow; Ewa Deelman; Wu Feng; Judy Qiu; Donna Russell; Elizabeth Stewart; Eugene Kolker
Journal:  OMICS       Date:  2011-04

4.  Introducing "Genomics and Precision Health".

Authors:  W Gregory Feero
Journal:  JAMA       Date:  2017-05-09       Impact factor: 56.272

5.  A comparison of algorithms for the pairwise alignment of biological networks.

Authors:  Connor Clark; Jugal Kalita
Journal:  Bioinformatics       Date:  2014-05-02       Impact factor: 6.937

6.  Graduate Training at the Interface of Computational and Experimental Biology: An Outcome Report from a Partnership of Volunteers between a University and a National Laboratory.

Authors:  Albrecht G von Arnim; Anamika Missra
Journal:  CBE Life Sci Educ       Date:  2017       Impact factor: 3.325

7.  Evidence that personal genome testing enhances student learning in a course on genomics and personalized medicine.

Authors:  Keyan Salari; Konrad J Karczewski; Louanne Hudgins; Kelly E Ormond
Journal:  PLoS One       Date:  2013-07-23       Impact factor: 3.240

Review 8.  Implementing genomic medicine in the clinic: the future is here.

Authors:  Teri A Manolio; Rex L Chisholm; Brad Ozenberger; Dan M Roden; Marc S Williams; Richard Wilson; David Bick; Erwin P Bottinger; Murray H Brilliant; Charis Eng; Kelly A Frazer; Bruce Korf; David H Ledbetter; James R Lupski; Clay Marsh; David Mrazek; Michael F Murray; Peter H O'Donnell; Daniel J Rader; Mary V Relling; Alan R Shuldiner; David Valle; Richard Weinshilboum; Eric D Green; Geoffrey S Ginsburg
Journal:  Genet Med       Date:  2013-01-10       Impact factor: 8.822

9.  Criteria for the use of omics-based predictors in clinical trials.

Authors:  Lisa M McShane; Margaret M Cavenagh; Tracy G Lively; David A Eberhard; William L Bigbee; P Mickey Williams; Jill P Mesirov; Mei-Yin C Polley; Kelly Y Kim; James V Tricoli; Jeremy M G Taylor; Deborah J Shuman; Richard M Simon; James H Doroshow; Barbara A Conley
Journal:  Nature       Date:  2013-10-17       Impact factor: 49.962

10.  Standard operating procedure for somatic variant refinement of sequencing data with paired tumor and normal samples.

Authors:  Erica K Barnell; Peter Ronning; Katie M Campbell; Kilannin Krysiak; Benjamin J Ainscough; Lana M Sheta; Shahil P Pema; Alina D Schmidt; Megan Richters; Kelsy C Cotto; Arpad M Danos; Cody Ramirez; Zachary L Skidmore; Nicholas C Spies; Jasreet Hundal; Malik S Sediqzad; Jason Kunisaki; Felicia Gomez; Lee Trani; Matthew Matlock; Alex H Wagner; S Joshua Swamidass; Malachi Griffith; Obi L Griffith
Journal:  Genet Med       Date:  2018-10-05       Impact factor: 8.822

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