DPP4ResearchGroup / SyntenyViz

R package to visualize Synteny across biological species

Home Page:https://dpp4researchgroup.github.io/SyntenyViz/

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SyntenyViz

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master Build Status
develop Build Status

What is SyntenyViz

SyntenyViz is a R package to visualise synteny across various biological species.

Motivation

Visualising the synteny across species not only enables intuitive examination and facilitates reconstruction effort of ancestral genomes, but also allow more direct interrogation of gene regulations and gene structures within a gene cluster.

Installation

Install from RStudio

  • Install and load devtools
install.packages("devtools")
library(devtools)
  • Install and load SyntenyViz from GitHub
install_github("DPP4ResearchGroup/SyntenyViz")
library(SyntenyViz)

To allow build vignettes, build_vignettes = TRUE options can be used as

install_github("DPP4ResearchGroup/SyntenyViz", build_vignettes = TRUE)
library(SyntenyViz)

Developing version can be accessed via develop as

install_github("DPP4ResearchGroup/SyntenyViz", ref = "develop")
library(SyntenyViz)

Quick Start for the Inpatients

Quick and minimum steps to get start a synteney conservation anaysis with SyntenyViz

  • Define an investigation range We need to firstly define an investigation range to cover the target range in gene coordinate. We will use a mouse dipeptidyl dipeptidase 4 gene (DPP4-mm) in this example, where DPP4-mm locates at chromosome number 2 between 62,330,073-62,412,231 bp.
# orgm is a handle for organism
orgmName <- "Mmusculus"
# mycoords.list is the investigation range handler
mycoords <- "2:6.0e7:6.5e7"
  • Convert mycoords.list into a GRange object
mycoords.gr <- SyntenyViz::coordFormat (mycoords.list = mycoords)

It is always a good habit to double check the input, so

mycoords.gr
  • Construct a single synteny graph
synvizPlot(mycoords.gr, orgmName)

Synteny around DPP4 gene in Humans

  • Construct a multi synteny graph

Pick a few of targets

orgm.1 <- "Hsapiens"
mycoords.list.1 <- "2:15.95e7:16.45e7"
orgm.2 <- "Mmusculus"
mycoords.list.2 <- "2:6.0e7:6.5e7"
orgm.3 <- "Rnorvegicus"
mycoords.list.3 <- "3:4.6e7:5.1e7"

Then construct a multiple synteny query

orgmsList <- orgmsCollection.init (orgmsList)
orgmsList <- orgmsAdd (orgm.1, orgmTxDB, mycoords.list.1, orgmsList)
orgmsList <- orgmsAdd (orgm.2, orgmTxDB, mycoords.list.2, orgmsList)
orgmsList <- orgmsAdd (orgm.3, orgmTxDB, mycoords.list.3, orgmsList)

Now, construct a comparative multi-synteny graph

multiplot <- multisynvizPlots(orgmsList)

Note: Due to heavy downloading and computing involved in this step, multisynvizPlots may take several minutes to complete.

Synteny Conservation around DPP4 gene between various Organisms

Examples

SyntenyViz also includes additional examples and training materials, which can be accessed via vignettes from RStudio

install_github("DPP4ResearchGroup/SyntenyViz", build_vignettes = TRUE)
browseVignettes("SyntenyViz")

OR a PDF can be accessed from SyntenyViz homepage.

Contribution

  1. Fork to your contributing account
  2. Create your feature branch (git checkout -b my-new-feature)
  3. Commit your changes (git commit -am 'Added some feature')
  4. Push to the feature branch (git push origin my-new-feature)
  5. Create a new PR

Issue Tracking

Issues and bugs can be raised and tracked through GitHub issue tracker for SyntenyViz.

Unit Testing

Travis CI testing (travis status) inplements R CMD check. The function integrity is checked by R native testthat, which can also be invoked by utility function devtools::test() from RStudio.

About

R package to visualize Synteny across biological species

https://dpp4researchgroup.github.io/SyntenyViz/

License:MIT License


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