README.md

In chemokine/OmicsSBGN: Overlay omics data onto SBGN pathway diagram

SBGNview

SBGNview is a tool set for visualizing omics data on SBGN pathway maps. Given omics data and a SBGN-ML file with layout information, SBGNview can display omics data as colors on glyphs and output image files. SBGNview provides extensive options to control glyph and edge features (e.g. color, line width etc.). To facilitate pathway based analysis, SBGNview also provides functions to extract glyph information and pairwise interactions from SBGN-ML files. SBGNview can map a large collection of gene, protein and compound ID typs to glyphs.

Introduction

Molecular pathways have been widely used in omics data analysis. We previously developed an R/BioConductor package called Pathview, which maps, integrates and visualizes omics data onto KEGG pathway graphs. Since its publication, Pathview has been widely used in numerous omics studies and analysis tools. Here we introduce the SBGNview package, which adopts Systems Biology Graphical Notation (SBGN)[@le2009systems] and greatly extends the Pathview project by supportting multiple major pathway databases besides KEGG.

Key features:

• Pathway diagram is drawn with SBGN notations

• Supports major pathway databases and user defined pathways.

• Extensive choices for graphical control.

• Pathway related data extraction and analysis

Installation

Prerequisites

SBGNview depends on the following packages:

• xml2: parse SBGN-ML files
• rsvg: convert svg files to other formats (pdf, png, ps). librsvg2 is needed to install rsvg. See this page for more details: https://github.com/jeroen/rsvg
• pathview: map between different ID types for gene and chemical compound.
• igraph: find shortest paths

Install SBGNview

```{r setup, eval = FALSE} if (!requireNamespace("BiocManager", quietly = TRUE)){ install.packages("BiocManager") } BiocManager::install( c("pathview", "xml2", "igraph", "rsvg"))

Install **SBGNview** itself through Bioconductor 
```{r install, eval = FALSE}
BiocManager::install(c("SBGNview"))

Install SBGNview through GitHub: ```{r install.1, eval = FALSE} install.packages("devtools") devtools::install_github("datapplab/SBGNview")

Clone the Git repository:
```{r clone.git, eval = FALSE}
git clone  https://github.com/datapplab/SBGNview.git

Quick example

```{r, echo = TRUE, eval = TRUE, results = 'hide', message = FALSE, warning = FALSE}

load demo dataset and pathway information of built-in collection of SBGN-ML files

library(SBGNview) data("gse16873.d","pathways.info") input.pathways <- find.pathways("Adrenaline and noradrenaline biosynthesis") SBGNview.obj <- SBGNview( gene.data = gse16873.d[,1:3], gene.id.type = "entrez", input.sbgn = input.pathways$pathway.id, output.file = "quick.start", output.formats = c("png") ) print(SBGNview.obj) ``` Two image files (a .svg file and a .pdf file) will be created in the current working directory.

Additional information

SBGN website: https://sbgn.github.io/

For any questions, please contact Xiaoxi Dong([e-mail]) or Weijun Luo([e-mail])

Citation

Nicolas Le Novère, Michael Hucka, Huaiyu Mi, Stuart Moodie, Falk Schreiber, Anatoly Sorokin, Emek Demir et al. The Systems Biology Graphical Notation Nature Biotechnology, 27(8):735-741, 2009

Luo, Weijun, and Cory Brouwer. "Pathview: an R/Bioconductor package for pathway-based data integration and visualization." Bioinformatics 29.14 (2013): 1830-1831.

chemokine/OmicsSBGN documentation built on June 27, 2019, 7:52 p.m.