Literature DB >> 24037425

Reproducibility of high-throughput mRNA and small RNA sequencing across laboratories.

Peter A C 't Hoen1, Marc R Friedländer, Jonas Almlöf, Michael Sammeth, Irina Pulyakhina, Seyed Yahya Anvar, Jeroen F J Laros, Henk P J Buermans, Olof Karlberg, Mathias Brännvall, Johan T den Dunnen, Gert-Jan B van Ommen, Ivo G Gut, Roderic Guigó, Xavier Estivill, Ann-Christine Syvänen, Emmanouil T Dermitzakis, Tuuli Lappalainen.   

Abstract

RNA sequencing is an increasingly popular technology for genome-wide analysis of transcript sequence and abundance. However, understanding of the sources of technical and interlaboratory variation is still limited. To address this, the GEUVADIS consortium sequenced mRNAs and small RNAs of lymphoblastoid cell lines of 465 individuals in seven sequencing centers, with a large number of replicates. The variation between laboratories appeared to be considerably smaller than the already limited biological variation. Laboratory effects were mainly seen in differences in insert size and GC content and could be adequately corrected for. In small-RNA sequencing, the microRNA (miRNA) content differed widely between samples owing to competitive sequencing of rRNA fragments. This did not affect relative quantification of miRNAs. We conclude that distributing RNA sequencing among different laboratories is feasible, given proper standardization and randomization procedures. We provide a set of quality measures and guidelines for assessing technical biases in RNA-seq data.

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Year:  2013        PMID: 24037425     DOI: 10.1038/nbt.2702

Source DB:  PubMed          Journal:  Nat Biotechnol        ISSN: 1087-0156            Impact factor:   54.908


  41 in total

1.  Evaluation of DNA microarray results with quantitative gene expression platforms.

Authors:  Roger D Canales; Yuling Luo; James C Willey; Bradley Austermiller; Catalin C Barbacioru; Cecilie Boysen; Kathryn Hunkapiller; Roderick V Jensen; Charles R Knight; Kathleen Y Lee; Yunqing Ma; Botoul Maqsodi; Adam Papallo; Elizabeth Herness Peters; Karen Poulter; Patricia L Ruppel; Raymond R Samaha; Leming Shi; Wen Yang; Lu Zhang; Federico M Goodsaid
Journal:  Nat Biotechnol       Date:  2006-09       Impact factor: 54.908

2.  Stem cell transcriptome profiling via massive-scale mRNA sequencing.

Authors:  Nicole Cloonan; Alistair R R Forrest; Gabriel Kolle; Brooke B A Gardiner; Geoffrey J Faulkner; Mellissa K Brown; Darrin F Taylor; Anita L Steptoe; Shivangi Wani; Graeme Bethel; Alan J Robertson; Andrew C Perkins; Stephen J Bruce; Clarence C Lee; Swati S Ranade; Heather E Peckham; Jonathan M Manning; Kevin J McKernan; Sean M Grimmond
Journal:  Nat Methods       Date:  2008-05-30       Impact factor: 28.547

3.  A tool for RNA sequencing sample identity check.

Authors:  Jinyan Huang; Jun Chen; Mark Lathrop; Liming Liang
Journal:  Bioinformatics       Date:  2013-04-04       Impact factor: 6.937

4.  A Bayesian framework to account for complex non-genetic factors in gene expression levels greatly increases power in eQTL studies.

Authors:  Oliver Stegle; Leopold Parts; Richard Durbin; John Winn
Journal:  PLoS Comput Biol       Date:  2010-05-06       Impact factor: 4.475

5.  A comparison of massively parallel nucleotide sequencing with oligonucleotide microarrays for global transcription profiling.

Authors:  James R Bradford; Yvonne Hey; Tim Yates; Yaoyong Li; Stuart D Pepper; Crispin J Miller
Journal:  BMC Genomics       Date:  2010-05-05       Impact factor: 3.969

6.  Biases in Illumina transcriptome sequencing caused by random hexamer priming.

Authors:  Kasper D Hansen; Steven E Brenner; Sandrine Dudoit
Journal:  Nucleic Acids Res       Date:  2010-04-14       Impact factor: 16.971

Review 7.  RNA-Seq: a revolutionary tool for transcriptomics.

Authors:  Zhong Wang; Mark Gerstein; Michael Snyder
Journal:  Nat Rev Genet       Date:  2009-01       Impact factor: 53.242

8.  A systematic comparison and evaluation of high density exon arrays and RNA-seq technology used to unravel the peripheral blood transcriptome of sickle cell disease.

Authors:  Nalini Raghavachari; Jennifer Barb; Yanqin Yang; Poching Liu; Kimberly Woodhouse; Daniel Levy; Christopher J O'Donnell; Peter J Munson; Gregory J Kato
Journal:  BMC Med Genomics       Date:  2012-06-29       Impact factor: 3.063

9.  edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.

Authors:  Mark D Robinson; Davis J McCarthy; Gordon K Smyth
Journal:  Bioinformatics       Date:  2009-11-11       Impact factor: 6.937

10.  SeqBuster, a bioinformatic tool for the processing and analysis of small RNAs datasets, reveals ubiquitous miRNA modifications in human embryonic cells.

Authors:  Lorena Pantano; Xavier Estivill; Eulàlia Martí
Journal:  Nucleic Acids Res       Date:  2009-12-11       Impact factor: 16.971

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  121 in total

1.  Multi-platform assessment of transcriptome profiling using RNA-seq in the ABRF next-generation sequencing study.

Authors:  Sheng Li; Scott W Tighe; Charles M Nicolet; Deborah Grove; Shawn Levy; William Farmerie; Agnes Viale; Chris Wright; Peter A Schweitzer; Yuan Gao; Dewey Kim; Joe Boland; Belynda Hicks; Ryan Kim; Sagar Chhangawala; Nadereh Jafari; Nalini Raghavachari; Jorge Gandara; Natàlia Garcia-Reyero; Cynthia Hendrickson; David Roberson; Jeffrey Rosenfeld; Todd Smith; Jason G Underwood; May Wang; Paul Zumbo; Don A Baldwin; George S Grills; Christopher E Mason
Journal:  Nat Biotechnol       Date:  2014-08-24       Impact factor: 54.908

2.  Normalization of RNA-seq data using factor analysis of control genes or samples.

Authors:  Davide Risso; John Ngai; Terence P Speed; Sandrine Dudoit
Journal:  Nat Biotechnol       Date:  2014-08-24       Impact factor: 54.908

3.  RNA Sequencing and Analysis.

Authors:  Kimberly R Kukurba; Stephen B Montgomery
Journal:  Cold Spring Harb Protoc       Date:  2015-04-13

4.  Global transcriptional start site mapping using differential RNA sequencing reveals novel antisense RNAs in Escherichia coli.

Authors:  Maureen K Thomason; Thorsten Bischler; Sara K Eisenbart; Konrad U Förstner; Aixia Zhang; Alexander Herbig; Kay Nieselt; Cynthia M Sharma; Gisela Storz
Journal:  J Bacteriol       Date:  2014-09-29       Impact factor: 3.490

5.  Polyester: simulating RNA-seq datasets with differential transcript expression.

Authors:  Alyssa C Frazee; Andrew E Jaffe; Ben Langmead; Jeffrey T Leek
Journal:  Bioinformatics       Date:  2015-04-28       Impact factor: 6.937

Review 6.  The role of regulatory variation in complex traits and disease.

Authors:  Frank W Albert; Leonid Kruglyak
Journal:  Nat Rev Genet       Date:  2015-02-24       Impact factor: 53.242

Review 7.  Reference standards for next-generation sequencing.

Authors:  Simon A Hardwick; Ira W Deveson; Tim R Mercer
Journal:  Nat Rev Genet       Date:  2017-06-19       Impact factor: 53.242

8.  Tools and best practices for data processing in allelic expression analysis.

Authors:  Stephane E Castel; Ami Levy-Moonshine; Pejman Mohammadi; Eric Banks; Tuuli Lappalainen
Journal:  Genome Biol       Date:  2015-09-17       Impact factor: 13.583

9.  Downregulation of the acetyl-CoA metabolic network in adipose tissue of obese diabetic individuals and recovery after weight loss.

Authors:  Harish Dharuri; Peter A C 't Hoen; Jan B van Klinken; Peter Henneman; Jeroen F J Laros; Mirjam A Lips; Fatiha El Bouazzaoui; Gert-Jan B van Ommen; Ignace Janssen; Bert van Ramshorst; Bert A van Wagensveld; Hanno Pijl; Ko Willems van Dijk; Vanessa van Harmelen
Journal:  Diabetologia       Date:  2014-08-07       Impact factor: 10.122

10.  Genetic variants in the PIWI-piRNA pathway gene DCP1A predict melanoma disease-specific survival.

Authors:  Weikang Zhang; Hongliang Liu; Jieyun Yin; Wenting Wu; Dakai Zhu; Christopher I Amos; Shenying Fang; Jeffrey E Lee; Yi Li; Jiali Han; Qingyi Wei
Journal:  Int J Cancer       Date:  2016-09-14       Impact factor: 7.396

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