Improving Validation Practices in “Omics” Research

“Omics” research poses acute challenges regarding how to enhance validation practices and eventually the utility of this rich information. Several strategies may be useful, including routine replication, public data and protocol availability, funding incentives, reproducibility rewards or penalties, and targeted repeatability checks.

[1]  P. Pye-Smith The Descent of Man, and Selection in Relation to Sex , 1871, Nature.

[2]  The Túngara Frog: A Study in Sexual Selection and Communication, Michael J. Ryan. University of Chicago Press, Chicago and London (1985), xv, +230. Price £27.95 hardback, £12.75 paperback , 1986 .

[3]  David R. Jones,et al.  A systematic review and evaluation of the use of tumour markers in paediatric oncology: Ewing's sarcoma and neuroblastoma. , 2003, Health technology assessment.

[4]  J. Ioannidis Why Most Published Research Findings Are False , 2005, PLoS medicine.

[5]  P. Donnelly,et al.  Replicating genotype–phenotype associations , 2007, Nature.

[6]  L. V. van't Veer,et al.  Clinical application of the 70-gene profile: the MINDACT trial. , 2008, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[7]  S. Paik,et al.  Development of the 21-gene assay and its application in clinical practice and clinical trials. , 2008, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[8]  M. Mann Comparative analysis to guide quality improvements in proteomics , 2009, Nature Methods.

[9]  K. Coombes,et al.  Deriving chemosensitivity from cell lines: Forensic bioinformatics and reproducible research in high-throughput biology , 2009, 1010.1092.

[10]  Robert E. Kearney,et al.  A HUPO test sample study reveals common problems in mass spectrometry-based proteomics , 2009, Nature Methods.

[11]  C. Ball,et al.  Repeatability of published microarray gene expression analyses , 2009, Nature Genetics.

[12]  S. Teutsch,et al.  The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) initiative: methods of the EGAPP Working Group , 2009, Genetics in Medicine.

[13]  Anne-Laure Boulesteix,et al.  Over-optimism in bioinformatics: an illustration , 2010, Bioinform..

[14]  D. Ransohoff Proteomics research to discover markers: what can we learn from Netflix? , 2010, Clinical chemistry.

[15]  M. Girolami,et al.  Recommendations for Biomarker Identification and Qualification in Clinical Proteomics , 2010, Science Translational Medicine.

[16]  K. Baggerly Disclose all data in publications. , 2010, Nature.

[17]  S. Sivapalaratnam,et al.  More outreach for young scientists. , 2010 .

[18]  John P. A. Ioannidis,et al.  An empirical assessment of validation practices for molecular classifiers , 2011, Briefings Bioinform..

[19]  J. Ioannidis,et al.  Public Availability of Published Research Data in High-Impact Journals , 2011, PloS one.

[20]  Andrew D. Johnson,et al.  Temporal Trends in Results Availability from Genome-Wide Association Studies , 2011, PLoS genetics.

[21]  D. Ransohoff,et al.  Biomarker studies: a call for a comprehensive biomarker study registry , 2011, Nature Reviews Clinical Oncology.

[22]  J. Ioannidis,et al.  Comparison of effect sizes associated with biomarkers reported in highly cited individual articles and in subsequent meta-analyses. , 2011, JAMA.