For instance, I think R is used by biologists, http://www.genomebiology.com/2004/5/10/R80 can the same analysis be done with SQL?
What R brings to the table are numerous statistical methods packages and some good data visualization packages. With just a few lines you can apply some sophisticated techniques and produce beautiful visualizations.
SQL can indeed do some complex analytics, but they're very difficult, so R is the easier platform for statistics and machine learning. I did a Coursera class recently in which we had to do matrix multiplication with SQL and even that was a brain teaser of a puzzle. The advantages of doing analytics within a database are (a) leveraging the query optimizer to speed up your analysis and (b) you can make the analysis available to other users of the same system via a view or stored procedure, so they don't have to do the same work twice.
you can use one in conjunction with the other;
R is a general programming language with a huge library of mostly statistical analysis routines.
SQL is a way to get data in/out of a database
You might want to use SQL for trivial analyses, and anything more, maybe use R. But you can use SQL from R to get the data.
SQL is great for choosing which columns to get out of multiple tables, somehow combined, as well as to filter which rows. If the end result is ready for R to use in modeling, that's great.
R can struggle to index and manipulate large datasets for combining/selecting columns and filtering rows, but that's the really nice stuff in SQL. They work well enough together and it's really no big deal to set both up.
Could you? Probably. Would you want to? I highly doubt it.