Difference between `apply_gradients` and `minimize` of optimizer in tensorflow

You can easily know from the link : https://www.tensorflow.org/get_started/get_started
(tf.train API part) that they actually do the same job.
The difference it that: if you use the separated functions( tf.gradients, tf.apply_gradients), you can apply other mechanism between them, such as gradient clipping.