Shiny genes and musical genes:
Adventures with Shiny apps and data sonification
DIB lab meeting
May 4, 2020
Dr. Rayna M. Harris
@raynamharris
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Slides https://speakerdeck.com/raynamharris/shiny-musical-genes
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Goals of lab meeting
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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
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What is the roadmap to building reproducible,
interactive plots for data exploration?
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2 plots with R code, R function & Shiny
(option to code along with GitHub and Binder)
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https://github.com/raynamharris/tutorials
2020-05-04-shinyMPG/
README.Rmd
server.R
ui.R
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Easy? Copy & paste R code
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https://github.com/raynamharris/tutorials/blob/master/2020-05-04-shinyMPG/README.md
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Medium? Write an function
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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
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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
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https://github.com/raynamharris/tutorials/blob/master/2020-05-04-shinyMPG/ui.R
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Discussion
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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
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Introduction to the “Birds, Brains, Banter” Lab
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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
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http://www.dovelovegenomics.org/
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What neuro-molecular changes underpin the
transition to parenthood?
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https://www.fatherly.com/love-money/tracy-morgan-parenting-quotes/
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Do external or internal cues drive the transition
to parenthood?
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Internal clock
External stimuli
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Can we visualize coordinated changes in gene
expression as a “transcriptional symphony”?
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Email attachment from Becca Sheet music made with R
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Finally, can we make the data easy to explore?
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Draft manuscript written for eLife, figures
formatted for Science :)
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https://github.com/macmanes-lab/DoveParentsRNAseq/blob/master/docs/manuscript/RJwrapper.pdf
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Work in progress/ Road map for today
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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
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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
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Fig2 What parental care candidate genes are
differentially expressed? Are they correlated?
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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
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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?
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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
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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
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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
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?
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Summary
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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
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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?