Evaluation of quantitative miRNA expression platforms in the microRNA quality control (miRQC) study

By Pieter Mestdagh, N. Hartmann, L. Baeriswyl, Ditte Andreasen, Nathalie Bernard, Caifu Chen, D. Cheo, Petula D'Andrade, M. DeMayo, L. Dennis and 26 more. Nature Methods, 2014

629 citations recorded by the source corpus.

Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/cc3015b92360964dca25f0a9f1c50005a12598ac

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cancer Research

1. Marcel E. Dinger
2. John S. Mattick

In Molecular Biology

1. Jesper L. V. Maag
2. Andreas Keller
3. Christina Backes
4. Pieter Mestdagh
5. Marcel E. Dinger
6. Jan Hellemans
7. Tobias Fehlmann
8. John S. Mattick

Citations in the corpus

• Benchmarking of RNA-sequencing analysis workflows using whole-transcriptome RT-qPCR expression data (2017, methodology): “To define a TPM cutoff, we applied a measure published previously in the miRNA Quality Control Study 22 , relying on single positive reduction in replicate experiments.”
• Distribution of miRNA expression across human tissues (2016, methodology): “We used a microarray platform for miRNA expression detection since this platform shows a high reproducibility as evidenced by the miRQC study (5).”