NiftyPET is an open source Python package for image reconstruction and analysis with uncertainty estimation as well as support for high-throughput parallel processing using GPU computing. The pipeline of the platform starts from MR and raw PET input data and is divided into the following processing stages: (1) list-mode data processing; (2) accurate attenuation coefficient map generation; (3) detector normalization; (4) exact forward and back projection between sinogram and image space; (5) estimation of reduced-variance random events; (6) high accuracy fully 3D estimation of scatter events; (7) voxel-based partial volume correction; (8) region- and voxel-level image analysis. GPU/Python infrastructure for PET image reconstruction and analysis. In its first release, it includes all the tools for processing the mMR list-mode data including generation of bootstrap replications. This software contains state-of-the-art routines for PET image reconstruction and analysis. All the core routines are implemented in CUDA C and then through C extensions are available as Python package nipet.