Literature DB >> 22210853

Differential expression--the next generation and beyond.

Paul L Auer1, Sanvesh Srivastava, R W Doerge.   

Abstract

RNA-sequencing (RNA-seq) technologies have not only pushed the boundaries of science, but also pushed the computational and analytic capacities of many laboratories. With respect to mapping and quantifying transcriptomes, RNA-seq has certainly established itself as the approach of choice. However, as the complexities of experiments continue to grow, there is still no standard practice that allows for design, processing, normalization, efficient dimension reduction and/or statistical analysis. With this in mind, we provide a brief review of some of the key challenges that are general to all RNA-seq experiments, namely experimental design, statistical analysis and dimensionality reduction.

Mesh:

Year:  2011        PMID: 22210853     DOI: 10.1093/bfgp/elr041

Source DB:  PubMed          Journal:  Brief Funct Genomics        ISSN: 2041-2649            Impact factor:   4.241


  13 in total

1.  Selecting between-sample RNA-Seq normalization methods from the perspective of their assumptions.

Authors:  Ciaran Evans; Johanna Hardin; Daniel M Stoebel
Journal:  Brief Bioinform       Date:  2018-09-28       Impact factor: 11.622

2.  Technical guide for applications of gene expression profiling in human health risk assessment of environmental chemicals.

Authors:  Julie A Bourdon-Lacombe; Ivy D Moffat; Michelle Deveau; Mainul Husain; Scott Auerbach; Daniel Krewski; Russell S Thomas; Pierre R Bushel; Andrew Williams; Carole L Yauk
Journal:  Regul Toxicol Pharmacol       Date:  2015-05-02       Impact factor: 3.271

3.  Comparison of normalization and differential expression analyses using RNA-Seq data from 726 individual Drosophila melanogaster.

Authors:  Yanzhu Lin; Kseniya Golovnina; Zhen-Xia Chen; Hang Noh Lee; Yazmin L Serrano Negron; Hina Sultana; Brian Oliver; Susan T Harbison
Journal:  BMC Genomics       Date:  2016-01-05       Impact factor: 3.969

4.  Large multiethnic Candidate Gene Study for C-reactive protein levels: identification of a novel association at CD36 in African Americans.

Authors:  Jaclyn Ellis; Ethan M Lange; Jin Li; Josee Dupuis; Jens Baumert; Jeremy D Walston; Brendan J Keating; Peter Durda; Ervin R Fox; Cameron D Palmer; Yan A Meng; Taylor Young; Deborah N Farlow; Renate B Schnabel; Carola S Marzi; Emma Larkin; Lisa W Martin; Joshua C Bis; Paul Auer; Vasan S Ramachandran; Stacey B Gabriel; Monte S Willis; James S Pankow; George J Papanicolaou; Jerome I Rotter; Christie M Ballantyne; Myron D Gross; Guillaume Lettre; James G Wilson; Ulrike Peters; Wolfgang Koenig; Russell P Tracy; Susan Redline; Alex P Reiner; Emelia J Benjamin; Leslie A Lange
Journal:  Hum Genet       Date:  2014-03-19       Impact factor: 4.132

5.  Exploring the shallow end; estimating information content in transcriptomics studies.

Authors:  Daniel J Kliebenstein
Journal:  Front Plant Sci       Date:  2012-09-10       Impact factor: 5.753

6.  Time series expression analyses using RNA-seq: a statistical approach.

Authors:  Sunghee Oh; Seongho Song; Gregory Grabowski; Hongyu Zhao; James P Noonan
Journal:  Biomed Res Int       Date:  2013-03-24       Impact factor: 3.411

7.  A comparison of methods for differential expression analysis of RNA-seq data.

Authors:  Charlotte Soneson; Mauro Delorenzi
Journal:  BMC Bioinformatics       Date:  2013-03-09       Impact factor: 3.169

8.  RNA profiles of porcine embryos during genome activation reveal complex metabolic switch sensitive to in vitro conditions.

Authors:  Olga Østrup; Gayla Olbricht; Esben Østrup; Poul Hyttel; Philippe Collas; Ryan Cabot
Journal:  PLoS One       Date:  2013-04-29       Impact factor: 3.240

9.  SOLiD-SAGE of endophyte-infected red fescue reveals numerous effects on host transcriptome and an abundance of highly expressed fungal secreted proteins.

Authors:  Karen V Ambrose; Faith C Belanger
Journal:  PLoS One       Date:  2012-12-28       Impact factor: 3.240

10.  Efficient experimental design and analysis strategies for the detection of differential expression using RNA-Sequencing.

Authors:  José A Robles; Sumaira E Qureshi; Stuart J Stephen; Susan R Wilson; Conrad J Burden; Jennifer M Taylor
Journal:  BMC Genomics       Date:  2012-09-17       Impact factor: 3.969

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