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Maximizing ecological and evolutionary insight in bisulfite sequencing data sets.

Publication ,  Journal Article
Lea, AJ; Vilgalys, TP; Durst, PAP; Tung, J
Published in: Nature ecology & evolution
August 2017

Genome-scale bisulfite sequencing approaches have opened the door to ecological and evolutionary studies of DNA methylation in many organisms. These approaches can be powerful. However, they introduce new methodological and statistical considerations, some of which are particularly relevant to non-model systems. Here, we highlight how these considerations influence a study's power to link methylation variation with a predictor variable of interest. Relative to current practice, we argue that sample sizes will need to increase to provide robust insights. We also provide recommendations for overcoming common challenges and an R Shiny app to aid in study design.

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Published In

Nature ecology & evolution

DOI

EISSN

2397-334X

ISSN

2397-334X

Publication Date

August 2017

Volume

1

Issue

8

Start / End Page

1074 / 1083

Related Subject Headings

  • Sulfites
  • Sequence Analysis, DNA
  • Sample Size
  • High-Throughput Nucleotide Sequencing
  • DNA Methylation
  • 4104 Environmental management
  • 3104 Evolutionary biology
  • 3103 Ecology
 

Citation

APA
Chicago
ICMJE
MLA
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Lea, A. J., Vilgalys, T. P., Durst, P. A. P., & Tung, J. (2017). Maximizing ecological and evolutionary insight in bisulfite sequencing data sets. Nature Ecology & Evolution, 1(8), 1074–1083. https://doi.org/10.1038/s41559-017-0229-0
Lea, Amanda J., Tauras P. Vilgalys, Paul A. P. Durst, and Jenny Tung. “Maximizing ecological and evolutionary insight in bisulfite sequencing data sets.Nature Ecology & Evolution 1, no. 8 (August 2017): 1074–83. https://doi.org/10.1038/s41559-017-0229-0.
Lea AJ, Vilgalys TP, Durst PAP, Tung J. Maximizing ecological and evolutionary insight in bisulfite sequencing data sets. Nature ecology & evolution. 2017 Aug;1(8):1074–83.
Lea, Amanda J., et al. “Maximizing ecological and evolutionary insight in bisulfite sequencing data sets.Nature Ecology & Evolution, vol. 1, no. 8, Aug. 2017, pp. 1074–83. Epmc, doi:10.1038/s41559-017-0229-0.
Lea AJ, Vilgalys TP, Durst PAP, Tung J. Maximizing ecological and evolutionary insight in bisulfite sequencing data sets. Nature ecology & evolution. 2017 Aug;1(8):1074–1083.

Published In

Nature ecology & evolution

DOI

EISSN

2397-334X

ISSN

2397-334X

Publication Date

August 2017

Volume

1

Issue

8

Start / End Page

1074 / 1083

Related Subject Headings

  • Sulfites
  • Sequence Analysis, DNA
  • Sample Size
  • High-Throughput Nucleotide Sequencing
  • DNA Methylation
  • 4104 Environmental management
  • 3104 Evolutionary biology
  • 3103 Ecology