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Evaluation of quantitative miRNA expression platforms in the microRNA quality control (miRQC) study.
Mestdagh, Pieter; Hartmann, Nicole; Baeriswyl, Lukas; Andreasen, Ditte; Bernard, Nathalie; Chen, Caifu; Cheo, David; D'Andrade, Petula; DeMayo, Mike; Dennis, Lucas; Derveaux, Stefaan; Feng, Yun; Fulmer-Smentek, Stephanie; Gerstmayer, Bernhard; Gouffon, Julia; Grimley, Chris; Lader, Eric; Lee, Kathy Y; Luo, Shujun; Mouritzen, Peter; Narayanan, Aishwarya; Patel, Sunali; Peiffer, Sabine; Rüberg, Silvia; Schroth, Gary; Schuster, Dave; Shaffer, Jonathan M; Shelton, Elliot J; Silveria, Scott; Ulmanella, Umberto; Veeramachaneni, Vamsi; Staedtler, Frank; Peters, Thomas; Guettouche, Toumy; Wong, Linda; Vandesompele, Jo.
Afiliação
  • Mestdagh P; Center for Medical Genetics, Ghent University, Ghent, Belgium.
  • Hartmann N; Novartis Institutes of Biomedical Research, Basel, Switzerland.
  • Baeriswyl L; Novartis Institutes of Biomedical Research, Basel, Switzerland.
  • Andreasen D; Exiqon, Vedbaek, Denmark.
  • Bernard N; Life Technologies, South San Francisco, California, USA.
  • Chen C; Life Technologies, South San Francisco, California, USA.
  • Cheo D; Quanta Biosciences, Inc., Gaithersburg, Maryland, USA.
  • D'Andrade P; Agilent Technologies, Inc., Santa Clara, California, USA.
  • DeMayo M; Affymetrix, Santa Clara, California, USA.
  • Dennis L; NanoString Technologies, Seattle, Washington, USA.
  • Derveaux S; WaferGen, San Francisco, California, USA.
  • Feng Y; Quanta Biosciences, Inc., Gaithersburg, Maryland, USA.
  • Fulmer-Smentek S; Agilent Technologies, Inc., Santa Clara, California, USA.
  • Gerstmayer B; Miltenyi Biotec, Bergisch Gladbach, Germany.
  • Gouffon J; Affymetrix, Santa Clara, California, USA.
  • Grimley C; NanoString Technologies, Seattle, Washington, USA.
  • Lader E; Qiagen, Fredrick, Maryland, USA.
  • Lee KY; Life Technologies, South San Francisco, California, USA.
  • Luo S; Illumina, Hayward, California, USA.
  • Mouritzen P; Exiqon, Vedbaek, Denmark.
  • Narayanan A; Strand Life Sciences, Bangalore, India.
  • Patel S; Life Technologies, South San Francisco, California, USA.
  • Peiffer S; Miltenyi Biotec, Bergisch Gladbach, Germany.
  • Rüberg S; Miltenyi Biotec, Bergisch Gladbach, Germany.
  • Schroth G; Illumina, Hayward, California, USA.
  • Schuster D; Quanta Biosciences, Inc., Gaithersburg, Maryland, USA.
  • Shaffer JM; Qiagen, Fredrick, Maryland, USA.
  • Shelton EJ; Life Technologies, South San Francisco, California, USA.
  • Silveria S; WaferGen, San Francisco, California, USA.
  • Ulmanella U; Life Technologies, South San Francisco, California, USA.
  • Veeramachaneni V; Strand Life Sciences, Bangalore, India.
  • Staedtler F; Novartis Institutes of Biomedical Research, Basel, Switzerland.
  • Peters T; Novartis Institutes of Biomedical Research, Basel, Switzerland.
  • Guettouche T; Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, USA.
  • Wong L; Life Technologies, South San Francisco, California, USA.
  • Vandesompele J; Center for Medical Genetics, Ghent University, Ghent, Belgium.
Nat Methods ; 11(8): 809-15, 2014 Aug.
Article em En | MEDLINE | ID: mdl-24973947
MicroRNAs are important negative regulators of protein-coding gene expression and have been studied intensively over the past years. Several measurement platforms have been developed to determine relative miRNA abundance in biological samples using different technologies such as small RNA sequencing, reverse transcription-quantitative PCR (RT-qPCR) and (microarray) hybridization. In this study, we systematically compared 12 commercially available platforms for analysis of microRNA expression. We measured an identical set of 20 standardized positive and negative control samples, including human universal reference RNA, human brain RNA and titrations thereof, human serum samples and synthetic spikes from microRNA family members with varying homology. We developed robust quality metrics to objectively assess platform performance in terms of reproducibility, sensitivity, accuracy, specificity and concordance of differential expression. The results indicate that each method has its strengths and weaknesses, which help to guide informed selection of a quantitative microRNA gene expression platform for particular study goals.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Controle de Qualidade / MicroRNAs Idioma: En Ano de publicação: 2014 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Controle de Qualidade / MicroRNAs Idioma: En Ano de publicação: 2014 Tipo de documento: Article