Literature DB >> 16646808

MergeMaid: R tools for merging and cross-study validation of gene expression data.

Leslie Cope1, Xiaogang Zhong, Elizabeth Garrett, Giovanni Parmigiani.   

Abstract

Cross-study validation of gene expression investigations is critical in genomic analysis. We developed an R package and associated object definitions to merge and visualize multiple gene expression datasets. Our merging functions use arbitrary character IDs and generate objects that can efficiently support a variety of joint analyses. Visualization tools support exploration and cross-study validation of the data, without requiring normalization across platforms. Tools include "integrative correlation'' plots that is, scatterplots of all pairwise correlations in one study against the corresponding pairwise correlations of another, both for individual genes and all genes combined. Gene-specific plots can be used to identify genes whose changes are reliably measured across studies. Visualizations also include scatterplots of gene-specific statistics quantifying relationships between expression and phenotypes of interest, using linear, logistic and Cox regression.

Entities:  

Year:  2004        PMID: 16646808     DOI: 10.2202/1544-6115.1046

Source DB:  PubMed          Journal:  Stat Appl Genet Mol Biol        ISSN: 1544-6115


  14 in total

1.  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

2.  Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap.

Authors:  Michael J Gandal; Jillian R Haney; Neelroop N Parikshak; Virpi Leppa; Gokul Ramaswami; Chris Hartl; Andrew J Schork; Vivek Appadurai; Alfonso Buil; Thomas M Werge; Chunyu Liu; Kevin P White; Steve Horvath; Daniel H Geschwind
Journal:  Science       Date:  2018-02-09       Impact factor: 47.728

3.  Transcriptional profiling of polycythemia vera identifies gene expression patterns both dependent and independent from the action of JAK2V617F.

Authors:  Windy Berkofsky-Fessler; Monica Buzzai; Marianne K-H Kim; Steven Fruchtman; Vesna Najfeld; Dong-Joon Min; Fabricio F Costa; Jared M Bischof; Marcelo B Soares; Melanie Jane McConnell; Weijia Zhang; Ross Levine; D Gary Gilliland; Raffaele Calogero; Jonathan D Licht
Journal:  Clin Cancer Res       Date:  2010-07-02       Impact factor: 12.531

4.  MULTI-WAY BLOCKMODELS FOR ANALYZING COORDINATED HIGH-DIMENSIONAL RESPONSES.

Authors:  Edoardo M Airoldi; Xiaopei Wang; Xiaodong Lin
Journal:  Ann Appl Stat       Date:  2013-12-23       Impact factor: 2.083

5.  Importing ArrayExpress datasets into R/Bioconductor.

Authors:  Audrey Kauffmann; Tim F Rayner; Helen Parkinson; Misha Kapushesky; Margus Lukk; Alvis Brazma; Wolfgang Huber
Journal:  Bioinformatics       Date:  2009-06-08       Impact factor: 6.937

6.  Determination and estimation of partitioning properties for substituted phosphates and thiophosphates.

Authors:  Yuying Dong; Guanghui Ding; Ying Cao; Zhuang Wang; Cheng Sun
Journal:  Environ Monit Assess       Date:  2008-05-23       Impact factor: 2.513

7.  Cross-platform Comparison of Two Pancreatic Cancer Phenotypes.

Authors:  Robert B Scharpf; Christine A Iacobuzio-Donahue; Leslie Cope; Ingo Ruczinski; Elizabeth Garrett-Mayer; Sindhu Lakkur; Domenico Campagna; Giovanni Parmigiani
Journal:  Cancer Inform       Date:  2010-11-01

8.  Molecular sub-classification of renal epithelial tumors using meta-analysis of gene expression microarrays.

Authors:  Thomas Sanford; Paul H Chung; Ariel Reinish; Vladimir Valera; Ramaprasad Srinivasan; W Marston Linehan; Gennady Bratslavsky
Journal:  PLoS One       Date:  2011-07-27       Impact factor: 3.240

9.  A measure of the signal-to-noise ratio of microarray samples and studies using gene correlations.

Authors:  David Venet; Vincent Detours; Hugues Bersini
Journal:  PLoS One       Date:  2012-12-12       Impact factor: 3.240

10.  Application of a correlation correction factor in a microarray cross-platform reproducibility study.

Authors:  Kellie J Archer; Catherine I Dumur; G Scott Taylor; Michael D Chaplin; Anthony Guiseppi-Elie; Geraldine Grant; Andrea Ferreira-Gonzalez; Carleton T Garrett
Journal:  BMC Bioinformatics       Date:  2007-11-15       Impact factor: 3.169

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