[R-bloggers] 10 R packages every data scientist should know about (and 6 more aRticles)

Do you have R packages pertaining to genomics that you might feel should make it to a 'Top 10 R packages for Bioinformatics' ? 

The yhat blog lists 10 R packages they wish they'd known about earlier. Drew Conway calls them "10 reasons to always start your analysis in R". They're all very useful R packages that every data scientist should be aware of. They are:

1. sqldf (for selecting from data frames using SQL)
2. forecast (for easy forecasting of time series)
3. plyr (data aggregation)
4. stringr (string manipulation)
5. Database connection packages RPostgreSQL, RMYSQL, RMongo, RODBC, RSQLite
6. lubridate (time and date manipulation)
7. ggplot2 (data visulization)
8. qcc (statistical quality control and QC charts)
9. reshape2 (data restructuring)
10. randomForest (random forest predictive models)

You can find links to all of these packages and tips on how to use them at link below.

yhat blog: 10 R packages I wish I knew about earlier