The EpiDiverse Plant Epigenome-Wide Association Studies (EWAS) Pipeline
Abstract
:1. Introduction
2. Results and Discussion
2.1. EpiDiverse EWAS Pipeline Workflow
2.1.1. Input Types for the EWAS Pipeline
2.1.2. Available Models
2.1.3. NA Filtering and Imputation with Methylation and SNP Datasets
2.1.4. Text and Graphical Outputs
2.2. Evaluation of the EpiDiverse EWAS Pipeline
2.2.1. Analysis of Q. lobata Dataset
2.2.2. Analysis of P. abies Dataset
DMP/DMR Analysis Considerations Using Different Callers
Filtering Missing Data after Uniting Individual Methylomes
The Intersection of Positions with All Inputs and Models for the CG Context
Removal of Genetic Variants That Might Be Interpreted as Significant Epigenetic Marks
Emodel Output Gene Ontology (GO) Analysis
CG Context G and GxE GO Analysis
2.3. Conclusions
3. Materials and Methods
3.1. The EpiDiverse EWAS Pipeline
3.2. Analysis of Q. lobata Data
3.3. Analysis of P. abies Data
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Input | Description | File(s) Formats | Required for Which Runs? | Required for Which Model? |
---|---|---|---|---|
sample sheet | Sample list, which includes sample names as key variables, single environment/phenotype data, and covariate(s). | txt | Required for all runs | Required for all models |
MPs | Context-specific methylation calls per sample. | bedGraph | Required for all runs | Required for all models |
DMPs | Context-specific differentially methylated positions. | bed | Required to run the pipeline with DMPs | Allowed for all models |
DMRs | Context-specific differentially methylated regions. | bed | Required to run the pipeline with DMRs | Allowed for all models |
Genetic variants | Genetic markers either in single or multisample formats. | vcf or vcf.gz | Required to run the G and GxE models | Required for G and GxE models |
CG | tmax 1 | tmin 2 | GSDD5 3 | CWD 4 |
---|---|---|---|---|
Gugger et al., 2016 | 38 | 1 | 0 | 0 |
EpiDiverse EWAS pipeline | 47 | 2 | 0 | 0 |
shared amount | 33 | 1 | not applicable | not applicable |
Shared % based on Gugger et al., 2016 | 86.42% | 100% | 100% | 100% |
CHG | ||||
Gugger et al., 2016 | 1 | 0 | 1 | 0 |
EpiDiverse EWAS pipeline | 1 | 0 | 0 | 1 |
shared amount | 1 | Not applicable | 0 | 0 |
Shared % based on Gugger et al., 2016 | 100% | 100% | 0% | 0% |
CHH | ||||
Gugger et al., 2016 | 1 | 0 | 1 | 0 |
EpiDiverse EWAS pipeline | 3 | 16 | 0 | 0 |
shared amount | 1 | not applicable | 0 | not applicable |
Shared % based on Gugger et al., 2016 | 100% | 0% | 0% | 100% |
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Share and Cite
Can, S.N.; Nunn, A.; Galanti, D.; Langenberger, D.; Becker, C.; Volmer, K.; Heer, K.; Opgenoorth, L.; Fernandez-Pozo, N.; Rensing, S.A. The EpiDiverse Plant Epigenome-Wide Association Studies (EWAS) Pipeline. Epigenomes 2021, 5, 12. https://doi.org/10.3390/epigenomes5020012
Can SN, Nunn A, Galanti D, Langenberger D, Becker C, Volmer K, Heer K, Opgenoorth L, Fernandez-Pozo N, Rensing SA. The EpiDiverse Plant Epigenome-Wide Association Studies (EWAS) Pipeline. Epigenomes. 2021; 5(2):12. https://doi.org/10.3390/epigenomes5020012
Chicago/Turabian StyleCan, Sultan Nilay, Adam Nunn, Dario Galanti, David Langenberger, Claude Becker, Katharina Volmer, Katrin Heer, Lars Opgenoorth, Noe Fernandez-Pozo, and Stefan A. Rensing. 2021. "The EpiDiverse Plant Epigenome-Wide Association Studies (EWAS) Pipeline" Epigenomes 5, no. 2: 12. https://doi.org/10.3390/epigenomes5020012