Single particle tomography (SPT or subtomogram averaging) offers a powerful alternative to traditional 2-D single particle reconstruction for studying conformationally or compositionally heterogeneous macromolecules. It can also provide direct observation (without labeling or staining) of complexes inside cells at nanometer resolution. The development of computational methods and tools for SPT remains an area of active research. Here we present the EMAN2.1 SPT toolbox, which offers a full SPT processing pipeline, from particle picking to post-alignment analysis of subtomogram averages, automating most steps. Different algorithm combinations can be applied at each step, providing versatility and allowing for procedural cross-testing and specimen-specific strategies. Alignment methods include all-vs-all, binary tree, iterative singlemodel refinement, multiple-model refinement, and self-symmetry alignment. An efficient angular search, Graphic Processing Unit (GPU) acceleration and both threaded and distributed parallelism are provided to speed up processing. Finally, automated simulations, per particle reconstruction of subtiltseries, and per-particle Contrast Transfer Function (CTF) correction have been implemented. Processing examples using both real and simulated data are shown for several structures.