Upgrade to Pro — share decks privately, control downloads, hide ads and more …

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
Tweet

More Decks by Rayna M Harris

Other Decks in Research

Transcript

  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

    View full-size slide

  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/

    View full-size slide

  3. From R function to Shiny apps
    3

    View full-size slide

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

    View full-size slide

  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

    View full-size slide

  6. Easy? Copy & paste R code
    6
    https://github.com/raynamharris/tutorials/blob/master/2020-05-04-shinyMPG/README.md

    View full-size slide

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

    View full-size slide

  8. Advanced? Build a Shiny app, part 1 of 2
    8
    https://github.com/raynamharris/tutorials/blob/master/2020-05-04-shinyMPG/shiny.R

    View full-size slide

  9. Advanced? Build a Shiny app, part 2 of 2
    9
    https://github.com/raynamharris/tutorials/blob/master/2020-05-04-shinyMPG/ui.R

    View full-size slide

  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?

    View full-size slide

  11. Pigeon Parental Care RNA-seq
    Project
    11

    View full-size slide

  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

    View full-size slide

  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/

    View full-size slide

  14. What neuro-molecular changes underpin the
    transition to parenthood?
    14
    https://www.fatherly.com/love-money/tracy-morgan-parenting-quotes/

    View full-size slide

  15. Do external or internal cues drive the transition
    to parenthood?
    15
    Internal clock
    External stimuli

    View full-size slide

  16. Can we visualize coordinated changes in gene
    expression as a “transcriptional symphony”?
    16
    Email attachment from Becca Sheet music made with R

    View full-size slide

  17. Finally, can we make the data easy to explore?
    17

    View full-size slide

  18. Draft manuscript written for eLife, figures
    formatted for Science :)
    18
    https://github.com/macmanes-lab/DoveParentsRNAseq/blob/master/docs/manuscript/RJwrapper.pdf

    View full-size slide

  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

    View full-size slide

  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

    View full-size slide

  21. Fig1 Tissue and sex are the greatest sources
    of variation in gene expression
    https://github.com/macmanes-lab/DoveParentsRNAseq analysis/fig1.Rmd 21

    View full-size slide

  22. Fig1 Controls are very different but sequential
    parental stages are quite similar
    https://github.com/macmanes-lab/DoveParentsRNAseq analysis/fig1.Rmd 22

    View full-size slide

  23. 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)

    View full-size slide

  24. 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

    View full-size slide

  25. Suppl. Candidate gene correlations (gonads)
    26
    https://github.com/macmanes-lab/DoveParentsRNAseq analysis/figure-2.Rmd

    View full-size slide

  26. Fig2 highlights candidate DEGs with most
    significant correlations per tissue
    https://github.com/macmanes-lab/DoveParentsRNAseq analysis/fig2.Rmd 27

    View full-size slide

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

    View full-size slide

  28. 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

    View full-size slide

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

    View full-size slide

  30. Fig3 Interactive candidate gene exploration
    and data sonification with Shiny
    https://raynamharris.shinyapps.io/musicalgenes/ 31

    View full-size slide

  31. Fig4 Prolactin (PRL) appears to explain all the
    variation in the pituitary
    https://github.com/macmanes-lab/DoveParentsRNAseq analysis/fig4.Rmd 32

    View full-size slide

  32. Suppl? Prolactin hormone and PRL gene
    expression are correlated
    https://github.com/macmanes-lab/DoveParentsRNAseq analysis/07_hormones.Rmd 33

    View full-size slide

  33. 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

    View full-size slide

  34. Fig4 External stimuli versus internal
    physiology hypothesis
    35

    View full-size slide

  35. 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

    View full-size slide

  36. Suppl? Some genes are correlated with PRL
    https://github.com/macmanes-lab/DoveParentsRNAseq lost in git history 37

    View full-size slide

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

    View full-size slide

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

    View full-size slide

  39. Fig4/5 PRL explains the more variation than
    external environment, in the pituitary
    https://github.com/macmanes-lab/DoveParentsRNAseq analysis/fig5.Rmd 40

    View full-size slide

  40. Figure 4? Or 4 and 5?
    41

    View full-size slide

  41. 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

    View full-size slide

  42. 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?

    View full-size slide