Assessing technical performance in differential gene expression experiments with external spike-in RNA control ratio mixtures (Q34440417)

2 August 2017

Assessing technical performance in differential gene expression experiments with external spike-in RNA control ratio mixtures (English)

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Nancy Stralis-Pavese

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Djork-Arné Clevert

Djork-Arné Clevert

5

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Gordon K Smyth

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Gordon K Smyth

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Weida Tong

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Leming Shi

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Christopher E Mason

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Paweł P Łabaj

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2 August 2017

Javier Santoyo-Lopez

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Huixiao Hong

Huixiao Hong

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Hans Binder

Hans Binder

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Joaquín Dopazo

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Joaquin Dopazo

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Robert A Setterquist

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P Scott Pine

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David P Kreil

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Nadereh Jafari

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Sarah A Munro

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Steven P Lund

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Ana Conesa

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Mario Fasold

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Sheng Li

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Yang Liao

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Simon M Lin

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Joseph Meehan

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Wei Shi

22

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Nancy Stralis-Pavese

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Zhenqiang Su

25

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Charles Wang

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Jian Wang

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Joshua Xu

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Zhan Ye

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Yong Yang

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Ying Yu

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Marc Salit

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language of work or name

English

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publication date

25 September 2014

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2 August 2017

Nature Communications

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5

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5125

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https://scigraph.springernature.com/pub.10.1038/ncomms6125

2 August 2017

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cites work

The External RNA Controls Consortium: a progress report.

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Standards in gene expression microarray experiments

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Exploring the use of internal and externalcontrols for assessing microarray technical performance

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Consolidated strategy for the analysis of microarray spike-in data

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Evaluation of external RNA controls for the assessment of microarray performance

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Monitoring global messenger RNA changes in externally controlled microarray experiments.

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Comparative analysis of RNA sequencing methods for degraded or low-input samples

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RNA-SeQC: RNA-seq metrics for quality control and process optimization

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Transposase mediated construction of RNA-seq libraries.

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Alternative expression analysis by RNA sequencing

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Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells

21 January 2018

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Synthetic spike-in standards for RNA-seq experiments

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The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

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Universal Reference RNA as a standard for microarray experiments

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Use of diagnostic accuracy as a metric for evaluating laboratory proficiency with microarray assays using mixed-tissue RNA reference samples

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Using RNA sample titrations to assess microarray platform performance and normalization techniques

21 January 2018

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Revisiting global gene expression analysis

21 January 2018

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The Subread aligner: fast, accurate and scalable read mapping by seed-and-vote

21 January 2018

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featureCounts: an efficient general purpose program for assigning sequence reads to genomic features

21 January 2018

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TopHat: discovering splice junctions with RNA-Seq

21 January 2018

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Fast and accurate short read alignment with Burrows-Wheeler transform

21 January 2018

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Variance stabilization applied to microarray data calibration and to the quantification of differential expression

21 January 2018

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G-stack modulated probe intensities on expression arrays - sequence corrections and signal calibration

21 January 2018

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A new summarization method for Affymetrix probe level data

21 January 2018

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Hybridization thermodynamics of NimbleGen microarrays.

21 January 2018

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Bioconductor: open software development for computational biology and bioinformatics

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Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation

21 January 2018

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

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Caveats and pitfalls of ROC analysis in clinical microarray research (and how to avoid them)

21 January 2018

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

21 January 2018

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7 January 2021

A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium

1 reference

https://api.crossref.org/works/10.1038%2FNCOMMS6125

7 January 2021

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

1 reference

https://api.crossref.org/works/10.1038%2FNCOMMS6125

7 January 2021

Detecting and correcting systematic variation in large-scale RNA sequencing data

1 reference

https://api.crossref.org/works/10.1038%2FNCOMMS6125

7 January 2021

Detecting differential expression in RNA-sequence data using quasi-likelihood with shrunken dispersion estimates

1 reference

https://api.crossref.org/works/10.1038%2FNCOMMS6125

7 January 2021

Identifiers

DOI

10.1038/NCOMMS6125

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Dimensions Publication ID

2 August 2017

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