Wed. Oct. 30, Geoduck DMR filtering

Summary of DMR analysis so far:

  1. Call methylation state from bismark data (mox script here)
  2. Call DMRs within individual samples (mox script here)
  3. Filter DMRs for those in at least 3/4 samples/group (R script here, R proj here)
  4. Filter DMRs for those significant at ANOVA uncorrected p.value < 0.1 R markdown script here, Rproj here

Summary of Step 4 above

Filtering DMRs for those significant at ANOVA uncorrected p.value < 0.1 from all 4 comparisons (all ambient samples, day10 samples, day 135 samples, and day 145 samples)

  • ANOVA significant all ambient MCmax30 DMR violinplots:

  • ANOVA significant day 10 MCmax30 DMR heatmap:
    • Heatmap key: Column color bar: cyan = ambient, light pink = low.pH, magenta = super.low.pH. heatmap cell color: Red = more methylation, blue = no methylation, black = no data.
  • ANOVA significant day 10 MCmax30 DMR violinplots:

  • ANOVA significant day 135 MCmax30 DMR heatmap:
    • Heatmap key: Column color bar: cyan = ambient, light pink = low.pH, magenta = super.low.pH. heatmap cell color: Red = more methylation, blue = no methylation, black = no data.
  • ANOVA significant day 135 MCmax30 DMR violinplots:

  • ANOVA significant day 145 MCmax30 DMR heatmap:
    • Heatmap key: Column color bar: cyan = ambient, light pink = low.pH, magenta = super.low.pH. heatmap cell color: Red = more methylation, blue = no methylation, black = no data.
  • ANOVA significant day 145 MCmax30 DMR violinplots:

Next steps:

  • visualize significant DMRs in IGV
  • Functional analysis of DMRs
Written on October 30, 2019