In Tsmnbx/ZooGVT: A Tool for Analyzing Animal Genomes

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

ZooGVT

The goal of ZooGVT is to visualize and understand what genes give rise or contribute to what anatomical features. The user is able to see what adjective they use as a feature for a animals in the BgeeDB database that have phenotype descriptions in Ensemble.

Description

ZooGVT allows users to visualize the various anatomical features related to a set of genes. This gives a better map of how certain genes translate into the animal features. These Genes can alter be extracted to compare differences between species. THis package allows easier access to the Uberon Ontolgy and aids in its use.

Installation

The development version from GitHub with:

# install.packages("devtools")
devtools::install_github("Tsmnbx/ZooGVT")

#May also need to do the below
#if (!requireNamespace("BiocManager", quietly = TRUE))
#  install.packages("BiocManager")

#BiocManager::install("topGO")

#if (!requireNamespace("BiocManager", quietly = TRUE))
#  install.packages("BiocManager")

#BiocManager::install("biomaRt")

#if (!requireNamespace("BiocManager", quietly = TRUE))
#  install.packages("BiocManager")

#BiocManager::install("BgeeDB")

#library(topGO)
#library(biomaRt)
#library(BgeeDB)

Example

This is a basic example which shows the UBERONids on could get for a Zebra fish with the descriptor "pectoral fin":

library(ZooGVT)


IdDataFrame<-ZooGVT::GetUberonIds("Danio_rerio","Zebrafish","pectoral fin")
IdDataFrame

This is a function that allows puts species wwritten in the correct format for this package:

library(ZooGVT)
NameVec<-GetNamesVec("Danio_rerio")

To run the Shiny app

runZooGVT()

If you get the following error "[1] "is it here" Warning: Error in GetNamesVec: could not find function "GetNamesVec"" run this code to run the shiney app

GetNamesVec<-function(name){
  indexComm<-match(name,ZooGVT::Species$Common_Name)
  indexSci<-match(name,ZooGVT::Species$Scientific_Name)
  names<-c()

  if(is.na(indexComm)== FALSE){
    index<-indexComm
    names<-append(names,ZooGVT::Species$Common_Name[index])
    names<-append(names,ZooGVT::Species$Scientific_Name[index])
    return(names)
  }

  if(is.na(indexSci)== FALSE){
    index<-indexSci
    names<-append(names,ZooGVT::Species$Common_Name[index])
    names<-append(names,ZooGVT::Species$Scientific_Name[index])
    return(names)
  }

}

Here is the package structure

print("├── DESCRIPTION
├── Danio_rerio_Bgee_14_1
│   ├── topAnat_AnatEntitiesNames_7955.tsv
│   ├── topAnat_AnatEntitiesRelationships_7955.tsv
│   └── topAnat_GeneToAnatEntities_7955_PRESENCESILVER.tsv
├── LICENSE
├── LICENSE.md
├── NAMESPACE
├── R
│   ├── GenesFromAnatomy.R
│   ├── GetUberonIds.R
│   ├── ListSpecies.R
│   └── data.R
├── README.Rmd
├── README.md
├── ZooGVT.Rproj
├── data
│   └── phyenotypeDescriptions.rda
├── inst
│   └── shiny-scripts
│       └── app.R
├── man
│   ├── GenesFromAnatomy.Rd
│   ├── GetUberonIds.Rd
│   ├── ListSpecies.Rd
│   ├── figures
│   │   └── README-pressure-1.png
│   └── phyenotypeDescriptions.Rd
├── release.tsv
├── species_Bgee_14_1.tsv
├── tests
│   ├── testthat
│   │   ├── release.tsv.tmp
│   │   └── test-ListSpecies.R
│   └── testthat.R
└── vignettes
    └── Introduction_ZooGVT.Rmd"
)

Contributions

The ListSpecies Function uses the BgeeDB package. The GetUberonIds function also made use of the BgeeDB package which uses topGO as well as the biomaRt for access to Ensembl. GenesFromAnatomy used all of these plus fmsb to produce a radar graph.

References

Komljenovic A, Roux J, Robinson-Rechavi M, and Bastian F (2016). BgeeDB, an R package for retrieval of curated expression datasets and for gene list enrichment tests. F1000Research

Bastian F et al. (2008). Bgee: Integrating and Comparing Heterogeneous Transcriptome Data Among Species. Data Integration Life Sci. Lecture Notes in Computer Science, 5109, 124-31

Charif, D. and Lobry, J.R. (2007)

Martin Morgan (2019). BiocManager: Access the Bioconductor Project Package Repository. R package version 1.30.10. https://CRAN.R-project.org/package=BiocManager

Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt. Steffen Durinck, Paul T. Spellman, Ewan Birney and Wolfgang Huber, Nature Protocols 4, 1184-1191 (2009).

BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis. Steffen Durinck, Yves Moreau, Arek Kasprzyk, Sean Davis, Bart De Moor, Alvis Brazma and Wolfgang Huber, Bioinformatics 21, 3439-3440 (2005).

Minato Nakazawa (2019). fmsb: Functions for Medical Statistics Book with some Demographic Data. R package version 0.7.0. https://CRAN.R-project.org/package=fmsb

Adrian Alexa and Jorg Rahnenfuhrer (2020). topGO: Enrichment Analysis for Gene Ontology. R package version 2.42.0.

R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.

“Learn Shiny.” Shiny, shiny.rstudio.com/tutorial/.

Holtz, Yan. “Basic Radar Chart.” – The R Graph Gallery, www.r-graph-gallery.com/142-basic-radar-chart.html.

Andrea Komljenovic, Julien Roux. BgeeDB, an R Package for Retrieval of Curated Expression Datasets and for Gene List Enrichment Tests, 27 Oct. 2020, bioconductor.org/packages/release/bioc/vignettes/BgeeDB/inst/doc/BgeeDB_Manual.html.