Dependent rounding, originating from the "pipage rounding" work of Ageev and Sviridenko, is now a fundamental algorithmic approach in combinatorial optimization. We survey this area, with an emphasis on the types of correlation inequalities that are achievable/desirable, and applications thereof. Topics covered include connections with matroids, matroid intersection, and scheduling, as well as how to handle situations where some amount of positive correlation is inevitable: the last part is recent joint work with David Harris, Thomas Pensyl, and Khoa Trinh, and arises in facility-location problems.