Literature DB >> 26028790

Integrative correlation: Properties and relation to canonical correlations.

Leslie Cope1, Daniel Q Naiman2, Giovanni Parmigiani3.   

Abstract

The integrative correlation coefficient was developed to facilitate the validation of expression microarray results in public datasets, by identifying genes that are reproducibly measured across studies and even across microarray platforms. In the current study, we develop a number of interesting and important mathematical and statistical properties of the integrative correlation coefficient, including a unique permutation-based null distribution with the unusual property that the variance does not shrink as the sample size increases, discussing how these findings impact its use and interpretation, and what they have to say about any method for identifying reproducible genes in a meta-analysis.

Entities:  

Keywords:  Bioinformatics; Correlation; Cross-study validation; Gene expression; Reproducibility; Statistics

Year:  2014        PMID: 26028790      PMCID: PMC4447241          DOI: 10.1016/j.jmva.2013.09.011

Source DB:  PubMed          Journal:  J Multivar Anal        ISSN: 0047-259X            Impact factor:   1.473


  27 in total

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Authors:  Evgeniy S Balakirev; Francisco J Ayala
Journal:  Annu Rev Genet       Date:  2003       Impact factor: 16.830

2.  Large scale comparison of global gene expression patterns in human and mouse.

Authors:  Xiangqun Zheng-Bradley; Johan Rung; Helen Parkinson; Alvis Brazma
Journal:  Genome Biol       Date:  2010-12-23       Impact factor: 13.583

3.  Cross-study validation and combined analysis of gene expression microarray data.

Authors:  Elizabeth Garrett-Mayer; Giovanni Parmigiani; Xiaogang Zhong; Leslie Cope; Edward Gabrielson
Journal:  Biostatistics       Date:  2007-09-14       Impact factor: 5.899

4.  A comparison of meta-analysis methods for detecting differentially expressed genes in microarray experiments.

Authors:  Fangxin Hong; Rainer Breitling
Journal:  Bioinformatics       Date:  2008-01-18       Impact factor: 6.937

5.  Biomarker detection in the integration of multiple multi-class genomic studies.

Authors:  Shuya Lu; Jia Li; Chi Song; Kui Shen; George C Tseng
Journal:  Bioinformatics       Date:  2009-12-04       Impact factor: 6.937

6.  Multigene expression-based predictors for sensitivity to Vorinostat and Velcade in non-small cell lung cancer.

Authors:  Alykhan S Nagji; Sang-Hoon Cho; Yuan Liu; Jae K Lee; David R Jones
Journal:  Mol Cancer Ther       Date:  2010-08-16       Impact factor: 6.261

Review 7.  The COXEN principle: translating signatures of in vitro chemosensitivity into tools for clinical outcome prediction and drug discovery in cancer.

Authors:  Steven C Smith; Alexander S Baras; Jae K Lee; Dan Theodorescu
Journal:  Cancer Res       Date:  2010-02-16       Impact factor: 12.701

Review 8.  Gene expression profiling reveals reproducible human lung adenocarcinoma subtypes in multiple independent patient cohorts.

Authors:  D Neil Hayes; Stefano Monti; Giovanni Parmigiani; C Blake Gilks; Katsuhiko Naoki; Arindam Bhattacharjee; Mark A Socinski; Charles Perou; Matthew Meyerson
Journal:  J Clin Oncol       Date:  2006-11-01       Impact factor: 44.544

9.  Comparing cDNA and oligonucleotide array data: concordance of gene expression across platforms for the NCI-60 cancer cells.

Authors:  Jae K Lee; Kimberly J Bussey; Fuad G Gwadry; William Reinhold; Gregory Riddick; Sandra L Pelletier; Satoshi Nishizuka; Gergely Szakacs; Jean-Phillipe Annereau; Uma Shankavaram; Samir Lababidi; Lawrence H Smith; Michael M Gottesman; John N Weinstein
Journal:  Genome Biol       Date:  2003-11-25       Impact factor: 13.583

10.  A strategy for predicting the chemosensitivity of human cancers and its application to drug discovery.

Authors:  Jae K Lee; Dmytro M Havaleshko; Hyungjun Cho; John N Weinstein; Eric P Kaldjian; John Karpovich; Andrew Grimshaw; Dan Theodorescu
Journal:  Proc Natl Acad Sci U S A       Date:  2007-07-31       Impact factor: 11.205

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  1 in total

1.  Tobacco exposure associated with oral microbiota oxygen utilization in the New York City Health and Nutrition Examination Study.

Authors:  Francesco Beghini; Audrey Renson; Christine P Zolnik; Ludwig Geistlinger; Mykhaylo Usyk; Thomas U Moody; Lorna Thorpe; Jennifer B Dowd; Robert Burk; Nicola Segata; Heidi E Jones; Levi Waldron
Journal:  Ann Epidemiol       Date:  2019-03-28       Impact factor: 3.797

  1 in total

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