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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

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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/

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From R function to Shiny apps 3

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

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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

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

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

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

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

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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?

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Pigeon Parental Care RNA-seq Project 11

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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

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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/

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

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

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

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

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

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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

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Fig1 Experimental Design 20 https://github.com/macmanes-lab/DoveParentsRNAseq analysis/fig1.Rmd N = 12-ish per sex * tissue * treatment 576 RNA-seq samples

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

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

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Figure 1 23

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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)

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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

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

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

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

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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

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

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

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

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

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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

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Fig4 External stimuli versus internal physiology hypothesis 35

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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

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

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

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

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

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Figure 4? Or 4 and 5? 41

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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

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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?

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Thanks! 44