In hyginn/BCB420.2019.ESA: Exploratory Systems Analysis Tools

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

# knitr knits in a new session with an empty global workspace after setting its
# working directory to ./vignettes. To make your package functions available in
# the vignette, you have to load the library. The following two lines should
# accomplish this without manual intervention:
pkgName <- trimws(gsub("^Package:", "", readLines("../DESCRIPTION")[1]))
library(pkgName, character.only = TRUE)

There are many links and references in this document. If you find anything here ambiguous, inaccurate, outdated, incomplete, or broken, please [file an issue](https://github.com/hyginn/BCB420.2019.ESA/issues)!

About this Vignette

This sample Vignette explains the BCB420.2019.STRINGExplore package. It aims to provide an instructive tutorial on the practical uses of the STRINGExplore tool and discuss applications and the interpretation of results.

The purpose of STRINGExplore is in the name-- it is exploratory. It aims to coordinate information available on disparate parts of the STRING database in a way that is visually pleasing and descriptive. These aims are achieved through the generation of a high-confidence gene interaction network and the leveraging of this visualization's tooltip system.

At its core, the aims of the descriptiveness of the system are as follows: 1. To inspire interaction 2. To develop the end-user's intuition for future hypotheses 3. To be easy to understand and navigate 4. To ameliorate the current state of hard-to-parse publication images of networks {IMAGE}

What's wrong with igraph?

STRINGExplore was created out of frustration about the complicated nature of setting up an igraph network in a visually pleasing and easy-to-process way. In regards to explorations of protein-protein interaction, igraph requires the user to be aware of the nature of their data before plotting it. With STRINGExplore, the nature of discovering the existence of high-confidence protein-protein actions is easier. Edges in network exist only if STRING computed for them a combined score >80% confidence, and the hover-over protein actions are listed in a human-readable way. On top of this, the tool outputs an object with this information in table form, for easy future analysis by the end-user.

Example usage

# Call the STRINGExplore tool
network <- STRINGExplore("PHALY")

# Table of nodes and their betweenness centrality scores, corresponding to the genes that are part of at # least 1 high-confidence edge:
network$nodes

# List of edges in network, representing STRING scores >=800
network$edges

# Visual output: interactive network (also plotted during tool's analysis)
network$network

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FUTURE WORK: Saving and publishing your network

Add functionality for STRINGExplore.save() using the visSave package - this saves the HTML of the network and all the dependencies of this analysis. Use this HTML on your research site for some snazzy interactive visualization axn