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Shiny for animal science:
project adatalab
Youngjun Na, PhD
Department of animal science and technology
Konkuk University
Email: ruminoreticulum@gmail.com
library(youngjunna)
# Information ----
Name <- ”Youngjun Na”
Family <- data.frame(
family = c(“wife”, “son”, “daughter”),
name = c(“Juhee”, “Sangwoo”, “Haon”)
)
# Link ----
[Github](“https://github.com/YoungjunNa”)
[TechnicalBlog](“https://youngjunna.github.io”)
# Research ----
Category <- “Animal science”
Category$major <- “Ruminant nutrition 🐄🐂🐏🦌”
Research <- lapply(AnimalScience, function(x) DataScience(x) * R(x))
# Summary ----
Animal %>%
Ruminant(for = c(“dairy”, “beef”, “environment”)) %>%
Nutrition(for = c(“productivity”, “behavior”, “welfare”)) %>%
Modeling(method = “ML”) %>%
R(for = c(“meta-analysis”, “data wrangling”, “visualization”, “Shiny”))
I’m an animal scientist
# Input
Nutrients
Environment
Genetics
# Output
Productivity
(milk, meat, reproduce)
Behavior
(rumination, moving)
Environment
(Greenhouse gas, manure)
Animal welfare
# Animal model
엄마가 상상하는 나의 모습
실제 나의 모습
R packages for Animal science:
Project animal data lab. (adatalab)
작은 모델 만들기 프로젝트
준비물:
§ Data
§ Computer (local PC or cloud)
§ 분석을 쉽게 만들어줄 tool
Project animal data lab. (adatalab)
§ https://github.com/adatalab
§ 동물 영양 연구 분석용 R package를 제작
사료 요구량 설정/결과분석 사료배합
Package: feed
§ https://github.com/adatalab/feed
§ Imports: rvest, ggplot2, dplyr
§ feed_list()
§ feed_search()
§ feed_info()
§ feed_compare()
Package: hanwoo
§ https://github.com/adatalab/hanwoo
§ Imports: XML, dplyr
§ hanwoo_info()
§ hanwoo_bull()
§ Functions for import the nutrient requirements of Hanwoo.
Package: dairyCattle
§ https://github.com/adatalab/dairyCattle
§ Imports: ggplot2, dplyr, janitor, timevis
§ mun_mp()
§ parturition()
https://youngjunna.github.io/adatalab/partur
ition
§ Functions for import the nutrient
requirements of dairy cattle.
Package: CH4goat
§ https://github.com/adatalab/CH4goat
§ Imports: neuralnet
§ The package contains two black-box model derived from the in vivo enteric
methane dataset using respiration-metabolism chamber system.
§ neuralnet::compute(model1, your_data)
Workflow for animal modeling
# Input
Nutrients
Environment
Genetics
# Output
Productivity
(milk, meat, reproduce)
Behavior
(rumination, moving)
Environment
(Greenhouse gas, manure)
Animal welfare
# Animal model
Shiny apps for Animal science
DairyLab
# Input
Cow performance test
(monthly)
# DairyLab
Data processing/cleansing
Visualization
Clustering
Modeling
# Output
Productivity
Animal welfare
Farm management
dairyCattle::read_cattle()
https://adatalab.github.io/dairylab-pro/
DairyLab
§ flexdashboard 패키지 기반(https://rmarkdown.rstudio.com/flexdashboard/index.html)
§ runtime: shiny
DairyLab
§ render*() 만 써도 대부분 flexdashboard에 적용 가능 == without *Output()
DairyLab
§ shinyApp() 의 응용
HanwooLab
# Input
Carcass info.
Genetic info.
hanwoo::hanwoo_info(“002123456789”)
+
hanwoo::hanwoo_bull(“1080”)
+
Rselenium + rvest
# HanwooLab
Data processing/cleansing
Modeling
Clustering
# Output
Productivity
Animal welfare
Farm management
https://adatalab.github.io/hanwoolab-example/ id: user pw: pass
HanwooLab
§ shinydashboard 패키지 기반(https://rstudio.github.io/shinydashboard/index.html)
§ shinyauthr 패키지를 통해 로그인 기능 구현(https://github.com/PaulC91/shinyauthr)
shinyauthr을 이용한 로그인 기능 구현(global)
shinyauthr을 이용한 로그인 기능 구현(ui)
shinyauthr을 이용한 로그인 기능 구현(server)
Github page + Shiny app
Github page에 shiny app 연결하기
§ Jekyll 기준
§ html 파일을 만들고 -> permalink 추가 -> iframe 적용
Github page에 shiny app 연결하기
---
permalink: /dairylab-pro/
---
<!DOCTYPE html>
<head>
</head>
<body>
<p>
<iframe src="https://youngjunna.shinyapps.io/dairylab-pro/" style="display:block; width:100vw; height: 100vh; border: 0">
It looks like your browser doesn't support iframes.
</iframe>
</p>
</body>
Thank you
Q&A

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Shiny for animal science

  • 1. Shiny for animal science: project adatalab Youngjun Na, PhD Department of animal science and technology Konkuk University Email: ruminoreticulum@gmail.com
  • 2. library(youngjunna) # Information ---- Name <- ”Youngjun Na” Family <- data.frame( family = c(“wife”, “son”, “daughter”), name = c(“Juhee”, “Sangwoo”, “Haon”) ) # Link ---- [Github](“https://github.com/YoungjunNa”) [TechnicalBlog](“https://youngjunna.github.io”)
  • 3. # Research ---- Category <- “Animal science” Category$major <- “Ruminant nutrition 🐄🐂🐏🦌” Research <- lapply(AnimalScience, function(x) DataScience(x) * R(x)) # Summary ---- Animal %>% Ruminant(for = c(“dairy”, “beef”, “environment”)) %>% Nutrition(for = c(“productivity”, “behavior”, “welfare”)) %>% Modeling(method = “ML”) %>% R(for = c(“meta-analysis”, “data wrangling”, “visualization”, “Shiny”))
  • 4. I’m an animal scientist # Input Nutrients Environment Genetics # Output Productivity (milk, meat, reproduce) Behavior (rumination, moving) Environment (Greenhouse gas, manure) Animal welfare # Animal model
  • 7. R packages for Animal science: Project animal data lab. (adatalab)
  • 8. 작은 모델 만들기 프로젝트 준비물: § Data § Computer (local PC or cloud) § 분석을 쉽게 만들어줄 tool
  • 9. Project animal data lab. (adatalab) § https://github.com/adatalab § 동물 영양 연구 분석용 R package를 제작 사료 요구량 설정/결과분석 사료배합
  • 10. Package: feed § https://github.com/adatalab/feed § Imports: rvest, ggplot2, dplyr § feed_list() § feed_search() § feed_info() § feed_compare()
  • 11. Package: hanwoo § https://github.com/adatalab/hanwoo § Imports: XML, dplyr § hanwoo_info() § hanwoo_bull() § Functions for import the nutrient requirements of Hanwoo.
  • 12. Package: dairyCattle § https://github.com/adatalab/dairyCattle § Imports: ggplot2, dplyr, janitor, timevis § mun_mp() § parturition() https://youngjunna.github.io/adatalab/partur ition § Functions for import the nutrient requirements of dairy cattle.
  • 13. Package: CH4goat § https://github.com/adatalab/CH4goat § Imports: neuralnet § The package contains two black-box model derived from the in vivo enteric methane dataset using respiration-metabolism chamber system. § neuralnet::compute(model1, your_data)
  • 14. Workflow for animal modeling # Input Nutrients Environment Genetics # Output Productivity (milk, meat, reproduce) Behavior (rumination, moving) Environment (Greenhouse gas, manure) Animal welfare # Animal model
  • 15. Shiny apps for Animal science
  • 16. DairyLab # Input Cow performance test (monthly) # DairyLab Data processing/cleansing Visualization Clustering Modeling # Output Productivity Animal welfare Farm management dairyCattle::read_cattle() https://adatalab.github.io/dairylab-pro/
  • 17. DairyLab § flexdashboard 패키지 기반(https://rmarkdown.rstudio.com/flexdashboard/index.html) § runtime: shiny
  • 18. DairyLab § render*() 만 써도 대부분 flexdashboard에 적용 가능 == without *Output()
  • 20. HanwooLab # Input Carcass info. Genetic info. hanwoo::hanwoo_info(“002123456789”) + hanwoo::hanwoo_bull(“1080”) + Rselenium + rvest # HanwooLab Data processing/cleansing Modeling Clustering # Output Productivity Animal welfare Farm management https://adatalab.github.io/hanwoolab-example/ id: user pw: pass
  • 21. HanwooLab § shinydashboard 패키지 기반(https://rstudio.github.io/shinydashboard/index.html) § shinyauthr 패키지를 통해 로그인 기능 구현(https://github.com/PaulC91/shinyauthr)
  • 22. shinyauthr을 이용한 로그인 기능 구현(global)
  • 24. shinyauthr을 이용한 로그인 기능 구현(server)
  • 25. Github page + Shiny app
  • 26. Github page에 shiny app 연결하기 § Jekyll 기준 § html 파일을 만들고 -> permalink 추가 -> iframe 적용
  • 27. Github page에 shiny app 연결하기 --- permalink: /dairylab-pro/ --- <!DOCTYPE html> <head> </head> <body> <p> <iframe src="https://youngjunna.shinyapps.io/dairylab-pro/" style="display:block; width:100vw; height: 100vh; border: 0"> It looks like your browser doesn't support iframes. </iframe> </p> </body>