Literature DB >> 22344273

Gene-expression measurement: variance-modeling considerations for robust data analysis.

Shankar Subramaniam1, Gene Hsiao.   

Abstract

System-wide measurements of gene expression by DNA microarray and, more recently, RNA-sequencing strategies have become de facto tools of modern biology and have led to deep understanding of biological mechanisms and pathways. However, analyses of the measurements have often ignored statistically robust methods that account for variance, resulting in misleading biological interpretations.

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Year:  2012        PMID: 22344273      PMCID: PMC4358796          DOI: 10.1038/ni.2244

Source DB:  PubMed          Journal:  Nat Immunol        ISSN: 1529-2908            Impact factor:   25.606


  15 in total

1.  A Bayesian framework for the analysis of microarray expression data: regularized t -test and statistical inferences of gene changes.

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Journal:  Bioinformatics       Date:  2001-06       Impact factor: 6.937

Review 2.  Reconstruction of cellular signalling networks and analysis of their properties.

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Authors:  Richard G Jenner; Richard A Young
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Review 4.  Microarray data analysis: from disarray to consolidation and consensus.

Authors:  David B Allison; Xiangqin Cui; Grier P Page; Mahyar Sabripour
Journal:  Nat Rev Genet       Date:  2006-01       Impact factor: 53.242

5.  RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays.

Authors:  John C Marioni; Christopher E Mason; Shrikant M Mane; Matthew Stephens; Yoav Gilad
Journal:  Genome Res       Date:  2008-06-11       Impact factor: 9.043

6.  Mapping and quantifying mammalian transcriptomes by RNA-Seq.

Authors:  Ali Mortazavi; Brian A Williams; Kenneth McCue; Lorian Schaeffer; Barbara Wold
Journal:  Nat Methods       Date:  2008-05-30       Impact factor: 28.547

Review 7.  Learning immunology from the yellow fever vaccine: innate immunity to systems vaccinology.

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Journal:  Nat Rev Immunol       Date:  2009-09-18       Impact factor: 53.106

8.  Preferred analysis methods for Affymetrix GeneChips. II. An expanded, balanced, wholly-defined spike-in dataset.

Authors:  Qianqian Zhu; Jeffrey C Miecznikowski; Marc S Halfon
Journal:  BMC Bioinformatics       Date:  2010-05-27       Impact factor: 3.169

9.  Mechanisms of human insulin resistance and thiazolidinedione-mediated insulin sensitization.

Authors:  D D Sears; G Hsiao; A Hsiao; J G Yu; C H Courtney; J M Ofrecio; J Chapman; S Subramaniam
Journal:  Proc Natl Acad Sci U S A       Date:  2009-10-19       Impact factor: 11.205

10.  Differential expression analysis for sequence count data.

Authors:  Simon Anders; Wolfgang Huber
Journal:  Genome Biol       Date:  2010-10-27       Impact factor: 13.583

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  9 in total

1.  The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance.

Authors:  Charles Wang; Binsheng Gong; Pierre R Bushel; Jean Thierry-Mieg; Danielle Thierry-Mieg; Joshua Xu; Hong Fang; Huixiao Hong; Jie Shen; Zhenqiang Su; Joe Meehan; Xiaojin Li; Lu Yang; Haiqing Li; Paweł P Łabaj; David P Kreil; Dalila Megherbi; Stan Gaj; Florian Caiment; Joost van Delft; Jos Kleinjans; Andreas Scherer; Viswanath Devanarayan; Jian Wang; Yong Yang; Hui-Rong Qian; Lee J Lancashire; Marina Bessarabova; Yuri Nikolsky; Cesare Furlanello; Marco Chierici; Davide Albanese; Giuseppe Jurman; Samantha Riccadonna; Michele Filosi; Roberto Visintainer; Ke K Zhang; Jianying Li; Jui-Hua Hsieh; Daniel L Svoboda; James C Fuscoe; Youping Deng; Leming Shi; Richard S Paules; Scott S Auerbach; Weida Tong
Journal:  Nat Biotechnol       Date:  2014-08-24       Impact factor: 54.908

2.  Statistical insights into major human muscular diseases.

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3.  Biomarkers of NAFLD progression: a lipidomics approach to an epidemic.

Authors:  D Lee Gorden; David S Myers; Pavlina T Ivanova; Eoin Fahy; Mano R Maurya; Shakti Gupta; Jun Min; Nathanael J Spann; Jeffrey G McDonald; Samuel L Kelly; Jingjing Duan; M Cameron Sullards; Thomas J Leiker; Robert M Barkley; Oswald Quehenberger; Aaron M Armando; Stephen B Milne; Thomas P Mathews; Michelle D Armstrong; Chijun Li; Willie V Melvin; Ronald H Clements; M Kay Washington; Alisha M Mendonsa; Joseph L Witztum; Ziqiang Guan; Christopher K Glass; Robert C Murphy; Edward A Dennis; Alfred H Merrill; David W Russell; Shankar Subramaniam; H Alex Brown
Journal:  J Lipid Res       Date:  2015-01-17       Impact factor: 5.922

4.  Transfer of clinically relevant gene expression signatures in breast cancer: from Affymetrix microarray to Illumina RNA-Sequencing technology.

Authors:  Debora Fumagalli; Alexis Blanchet-Cohen; David Brown; Christine Desmedt; David Gacquer; Stefan Michiels; Françoise Rothé; Samira Majjaj; Roberto Salgado; Denis Larsimont; Michail Ignatiadis; Marion Maetens; Martine Piccart; Vincent Detours; Christos Sotiriou; Benjamin Haibe-Kains
Journal:  BMC Genomics       Date:  2014-11-21       Impact factor: 3.969

5.  New Insights Into Lignification via Network and Multi-Omics Analyses of Arogenate Dehydratase Knock-Out Mutants in Arabidopsis thaliana.

Authors:  Kim K Hixson; Joaquim V Marques; Jason P Wendler; Jason E McDermott; Karl K Weitz; Therese R Clauss; Matthew E Monroe; Ronald J Moore; Joseph Brown; Mary S Lipton; Callum J Bell; Ljiljana Paša-Tolić; Laurence B Davin; Norman G Lewis
Journal:  Front Plant Sci       Date:  2021-05-25       Impact factor: 6.627

6.  Robust modeling of differential gene expression data using normal/independent distributions: a Bayesian approach.

Authors:  Mojtaba Ganjali; Taban Baghfalaki; Damon Berridge
Journal:  PLoS One       Date:  2015-04-24       Impact factor: 3.240

7.  Consistency of biological networks inferred from microarray and sequencing data.

Authors:  Veronica Vinciotti; Ernst C Wit; Rick Jansen; Eco J C N de Geus; Brenda W J H Penninx; Dorret I Boomsma; Peter A C 't Hoen
Journal:  BMC Bioinformatics       Date:  2016-06-24       Impact factor: 3.169

8.  CEMiTool: a Bioconductor package for performing comprehensive modular co-expression analyses.

Authors:  Pedro S T Russo; Gustavo R Ferreira; Lucas E Cardozo; Matheus C Bürger; Raul Arias-Carrasco; Sandra R Maruyama; Thiago D C Hirata; Diógenes S Lima; Fernando M Passos; Kiyoshi F Fukutani; Melissa Lever; João S Silva; Vinicius Maracaja-Coutinho; Helder I Nakaya
Journal:  BMC Bioinformatics       Date:  2018-02-20       Impact factor: 3.169

9.  Plasmacytoid, conventional, and monocyte-derived dendritic cells undergo a profound and convergent genetic reprogramming during their maturation.

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  9 in total

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