Assessment of pharmacogenomic agreement.

F1000Research

Volumn 5, Issue , 2016, Pages

  Safikhani, Zhaleh ^a,b   El Hachem, Nehme ^c   Quevedo, Rene ^a,b   Smirnov, Petr ^a   Goldenberg, Anna ^d,e   Birkbak, Nicolai Juul ^f   Mason, Christopher ^g,h,i   Hatzis, Christos ^j,k   Shi, Leming ^l,m   Aerts, Hugo J W L ^n,o   Quackenbush, John ⁿ   Haibe Kains, Benjamin ^a,b,e  

^a PRINCESS MARGARET HOSPITAL   (Canada)

^b UNIVERSITY OF TORONTO   (Canada)

^c CLIN RESEARCH INSTITUTE OF MONTREAL   (Canada)

^d HOSPITAL FOR SICK CHILDREN   (Canada)

^e UNIVERSITY OF TORONTO   (Canada)

^f UNIVERSITY COLLEGE LONDON   (United Kingdom)

^g WEILL CORNELL MEDICAL COLLEGE   (United States)

^h HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine   (United States)

ⁱ FEIL FAMILY BRAIN AND MIND RESEARCH INSTITUTE   (United States)

^j YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^k YALE CANCER CENTER   (United States)

^l FUDAN UNIVERSITY   (China)

^m UNIVERSITY OF ARKANSAS FOR MEDICAL SCIENCES   (United States)

ⁿ DANA FARBER CANCER INSTITUTE   (United States)

^o HARVARD MEDICAL SCHOOL   (United States)

more..

Author keywords

[No Author keywords available]

Indexed keywords

LAPATINIB;

AREA UNDER THE CURVE; ARTICLE; DRUG ACTIVITY; DRUG RESPONSE; DRUG SENSITIVITY; GENE EXPRESSION; IC50; MICROARRAY ANALYSIS; PHARMACOGENOMICS;

EID: 85010961092     PISSN: None     EISSN: 20461402     Source Type: Journal    
DOI: 10.12688/F1000RESEARCH.8705.1     Document Type: Article

References (13)

1. Garnett MJ, Edelman EJ, Heidorn SJ, et al.: Systematic identification of genomic markers of drug sensitivity in cancer cells. Nature. 2012; 483(7391): 570-575.
2. Barretina J, Caponigro G, Stransky N, et al.: The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature. 2012; 483(7391): 603-607.
3. Haibe-Kains B, El-Hachem N, Birkbak NJ, et al.: Inconsistency in large pharmacogenomic studies. Nature. 2013; 504(7480): 389-393.
4. Cancer Cell Line Encyclopedia Consortium, Genomics of Drug Sensitivity in Cancer Consortium: Pharmacogenomic agreement between two cancer cell line data sets. Nature. 2015; 528(7580): 84-87.
5. SEQC/MAQC-III Consortium: A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium. Nat Biotechnol. 2014; 32(9): 903-914.
6. MAQC Consortium, Shi L, Reid LH, et al.: The MicroArray Quality Control (MAQC) project shows inter-and intraplatform reproducibility of gene expression measurements. Nat Biotechnol. 2006; 24(9): 1151-1161.
7. Shi L, Campbell G, Jones WD, et al.: The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarraybased predictive models. Nat Biotechnol. 2010; 28(8): 827-838.
8. Li S, Tighe SW, Nicolet CM, et al.: Multi-platform assessment of transcriptome profiling using RNA-seq in the ABRF next-generation sequencing study. Nat Biotechnol. 2014; 32(9): 915-925.
9. Sim J, Wright CC: The kappa statistic in reliability studies: use, interpretation, and sample size requirements. Phys Ther. 2005; 85(3): 257-268.
10. Safikhani Z, Freeman M, Smirnov P, et al.: Revisiting inconsistency in large pharmacogenomic studies. bioRxiv. 2015; 026153.
11. Hudson AM, Yates T, Li Y, et al.: Discrepancies in cancer genomic sequencing highlight opportunities for driver mutation discovery. Cancer Res. 2014; 74(22): 6390-6396.
12. Smirnov P, Safikhani Z, El-Hachem N, et al.: PharmacoGx: An R package for analysis of large pharmacogenomic datasets. Bioinformatics. 2015; 32(8): 1244-1246. pii: btv723.
13. Safikhani Z, El-Hachem N, Quevedo R, et al.: Dataset: Assessment of pharmacogenomic agreement. Open Science Framework. 2016.