In many applications, the manipulations require only part of the degrees of freedom (DOFs) of the end-effector, or some DOFs are more important than the rest. We name these applications prioritized manipulations. The end-effector's DOFs are divided into those which are critical and must be controlled as precisely as possible, and those which have loose specifications, so their tracking performance can be traded-off to achieve other needs. In this paper, we derive a formulation for partitioning the task space into major and secondary task directions and finding the velocity and static force mappings that precisely accomplish the major task and locally optimize some secondary goals. The techniques are tested on a 6-DOF parallel robot performing a 2-DOF tracking task.