This paper proposes novel audio effects based on manipulating an audio signal in a representation domain provided by non-negative matrix factorization (NMF). Critical-band magnitude spectrograms Y of sounds are first factorized into a product of two lower-rank matrices so that Y ≈ BG. The parameter matrices B and G are then processed in order to achieve the desired effect. Three classes of effects were investigated: 1) dynamic range compression (or expansion) of the component spectra or gains, 2) effects based on rank-ordering the components (colums of B and the corresponding rows of G) according to acoustic features extracted from them, and then weighting each component according to its rank, and 3) distortion effects based on controlling the amount of components (and thus the reconstruction error) in the above linear approximation. The subjective quality of the effects was assessed in a listening test.