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Shiny Musical Genes

Shiny Musical Genes

Shiny genes and musical genes: Adventures with Shiny apps and data sonification. Figures and results correspond to version 3 of this GitHub repository containing the research compendium. https://github.com/macmanes-lab/DoveParentsRNAseq/releases/tag/v0.3


Rayna M Harris

May 04, 2020


  1. Shiny genes and musical genes: Adventures with Shiny apps and

    data sonification DIB lab meeting May 4, 2020 Dr. Rayna M. Harris @raynamharris 1 Slides https://speakerdeck.com/raynamharris/shiny-musical-genes
  2. Goals of lab meeting 2 1. Discuss R functions and

    Shiny apps https://github.com/raynamharris/tutorials 2. Get feedback on four figures-in-progress for the pigeon parental care RNA-seq project https://github.com/macmanes-lab/DoveParentsRNAseq 3. Get feedback on “Musical Genes” Shiny app https://raynamharris.shinyapps.io/musicalgenes/
  3. From R function to Shiny apps 3

  4. What is the roadmap to building reproducible, interactive plots for

    data exploration? 4
  5. 2 plots with R code, R function & Shiny (option

    to code along with GitHub and Binder) 5 https://github.com/raynamharris/tutorials 2020-05-04-shinyMPG/ README.Rmd server.R ui.R
  6. Easy? Copy & paste R code 6 https://github.com/raynamharris/tutorials/blob/master/2020-05-04-shinyMPG/README.md

  7. Medium? Write an function 7 https://github.com/raynamharris/tutorials/blob/master/2020-05-04-shinyMPG/README.md

  8. Advanced? Build a Shiny app, part 1 of 2 8

  9. Advanced? Build a Shiny app, part 2 of 2 9

  10. Discussion 10 1. What are the pre-reqs to learning Shiny?

    2. What is needed to make this a real tutorial? 3. How could the code be improved? 4. What are alternative approaches?
  11. Pigeon Parental Care RNA-seq Project 11

  12. Introduction to the “Birds, Brains, Banter” Lab 12 Calisi &

    a Working Group of Mothers in Science 2018 PNAS Data Commons (DCPPC) Photo by Tim McConville Molecular neuroscience of parental care in pigeons
  13. The Pigeon Parental Care Team Dr. Rayna Harris Dr. Suzanne

    Austin Dr. Andrew Lang Dr. Matthew MacManes Dr. Rebecca Calisi Rechelle Viernes Dr. Jesse Krause (Wingfield Lab) April Booth Victoria Farrar University of California, Davis University of New Hampshire 13 http://www.dovelovegenomics.org/
  14. What neuro-molecular changes underpin the transition to parenthood? 14 https://www.fatherly.com/love-money/tracy-morgan-parenting-quotes/

  15. Do external or internal cues drive the transition to parenthood?

    15 Internal clock External stimuli
  16. Can we visualize coordinated changes in gene expression as a

    “transcriptional symphony”? 16 Email attachment from Becca Sheet music made with R
  17. Finally, can we make the data easy to explore? 17

  18. Draft manuscript written for eLife, figures formatted for Science :)

    18 https://github.com/macmanes-lab/DoveParentsRNAseq/blob/master/docs/manuscript/RJwrapper.pdf
  19. Work in progress/ Road map for today 19 Figure 1:

    Broad patterns of variation in gene expression Figure 2: Candidate gene expression Figure 3: Shiny! Music! Figure 4: Pituitary PRL Photo taken on Sunday, May 3, 2020
  20. Fig1 Experimental Design 20 https://github.com/macmanes-lab/DoveParentsRNAseq analysis/fig1.Rmd N = 12-ish per

    sex * tissue * treatment 576 RNA-seq samples
  21. Fig1 Tissue and sex are the greatest sources of variation

    in gene expression https://github.com/macmanes-lab/DoveParentsRNAseq analysis/fig1.Rmd 21
  22. Fig1 Controls are very different but sequential parental stages are

    quite similar https://github.com/macmanes-lab/DoveParentsRNAseq analysis/fig1.Rmd 22
  23. Figure 1 23

  24. Fig2 What parental care candidate genes are differentially expressed? Are

    they correlated? 24 http://www.informatics.jax.org/go/term/GO:0060746 Curley & Champagne 2012, Gene Ontology (GO)
  25. Table 1. Half of parental care genes are differentially expressed

    between sequential parental stages from bldg to n9. https://github.com/macmanes-lab/DoveParentsRNAseq results/table1.csv 25
  26. Suppl. Candidate gene correlations (gonads) 26 https://github.com/macmanes-lab/DoveParentsRNAseq analysis/figure-2.Rmd

  27. Fig2 highlights candidate DEGs with most significant correlations per tissue

    https://github.com/macmanes-lab/DoveParentsRNAseq analysis/fig2.Rmd 27
  28. Figure 2? What else? 28 https://github.com/macmanes-lab/DoveParentsRNAseq analysis/figure-2.Rmd

  29. Sonification is the use of non-speech audio to convey information

    or perceptualize data 29 https://github.com/macmanes-lab/DoveParentsRNAseq analysis/figure-2.Rmd
  30. Fig2/3 From median counts to music notes https://github.com/macmanes-lab/DoveParentsRNAseq analysis/fig2.Rmd 30

  31. Fig3 Interactive candidate gene exploration and data sonification with Shiny

    https://raynamharris.shinyapps.io/musicalgenes/ 31
  32. Fig4 Prolactin (PRL) appears to explain all the variation in

    the pituitary https://github.com/macmanes-lab/DoveParentsRNAseq analysis/fig4.Rmd 32
  33. Suppl? Prolactin hormone and PRL gene expression are correlated https://github.com/macmanes-lab/DoveParentsRNAseq

    analysis/07_hormones.Rmd 33
  34. Fig3 females and males show similar pattern, rise during incubation

    then fall after hatch https://github.com/macmanes-lab/DoveParentsRNAseq analysis/07_hormones.Rmd 34 males females
  35. Fig4 External stimuli versus internal physiology hypothesis 35

  36. 36 https://github.com/macmanes-lab/DoveParentsRNAseq analysis/fig4.Rmd Fig4 PRL levels have a bigger effect

    on pituitary gene expression than eggs vs. chicks females males
  37. Suppl? Some genes are correlated with PRL https://github.com/macmanes-lab/DoveParentsRNAseq lost in

    git history 37
  38. Fig4/5: Experimental manipulations https://github.com/macmanes-lab/DoveParentsRNAseq analysis/fig5.Rmd 38

  39. Fig4/5 Hypothesis testing? https://github.com/macmanes-lab/DoveParentsRNAseq analysis/fig5.Rmd 39

  40. Fig4/5 PRL explains the more variation than external environment, in

    the pituitary https://github.com/macmanes-lab/DoveParentsRNAseq analysis/fig5.Rmd 40
  41. Figure 4? Or 4 and 5? 41

  42. Summary 42 Figure 1: Broad patterns of variation in gene

    expression Figure 2: Candidate gene expression Figure 3: Shiny! Music! Figure 4: Pituitary PRL Photo taken on Sunday, May 3, 2020
  43. Discussion 43 1. What is missing? 2. What should be

    removed? 3. How can the figures be improved? 4. How can the shiny app be improved? 5. Next steps?
  44. Thanks! 44