Next-generation sequencing data interpretation: enhancing reproducibility and accessibility

By Anton Nekrutenko, James Taylor. Nature reviews genetics, 2012

335 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/ecccdd7037bff36cd08043cf0ae7a38e01e744a5

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Citations in the corpus

Environmental DNA metabarcoding: Transforming how we survey animal and plant communities (2017, background): “As eDNA applications continue to develop, all procedures used in the field, laboratory and during bioinformatic data processing require a strong commitment to transparency on the part of researchers (Nekrutenko & Taylor, 2012).”
Ten Simple Rules for Reproducible Computational Research (2013, background): “…has recently been exemplified through studies showing that scientific papers commonly leave out experimental details essential for reproduction [5], studies showing difficulties with replicating published experimental results [6], an increase in retracted papers [7], and through a high number…”
Reproducibility in Science: Improving the Standard for Basic and Preclinical Research (2015, positive): “Similar observations have been made by others.(23,25) An analysis of 500 papers in the 50 top journals across scientific fields (those with highest impact factors) revealed only 9% deposited full primary data online.”
ENCODE data at the ENCODE portal (2015, background): “As discussions about the issues of reproducibility and reusability of genomic data are becoming more significant (13,14), the new ENCODE Portal serves to communicate”
ngs.plot: Quick mining and visualization of next-generation sequencing data by integrating genomic databases (2014, background): “The bottleneck is now in the processing and interpretation of the massive amount of data that are being generated [70,71].”