R is a free open-source software with rapidly increasing use in many research fields, including social science. As of early March, 2016, there are 8,030 packages that can be downloaded for use. Of those, there are at least 15 social network analysis tools, including modules for generic social network analysis (sna, igraph), more in-depth statistical methods for social network analysis (staTools, statnet), simulation packages (NetSim, RSiena), and more specialized tools for particular analysis of social networks (temporal analysis, multiplex analysis, ego-centric measures, etc). Fast growing diversity of new methodologies in social network research is quickly reflected in various evolving modules. One of the major strength of R is its flexibility of using different kinds of packages in an integrated system, fully connecting with vast number of other modules, including standard statistical methods, various regression models, complex survey sampling and analysis, multivariate analyses, structural equation modeling, data mining approaches, and specialized graphics. Relative weakness in the user interface has also been improved by some recent developments such as R Commander for menu-driven standard statistics and R studio for friendly interactive programming environment. This paper gives an overview of the various social network analysis packages in R, and demonstrates how these can be used in combinations with more traditional statistical methods as well as diverse graphical analyses.