The emergence of high-throughput experiments and high-resolution computational predictions has led to an explosion in the quality and volume of protein sequence annotations at proteomic scales. Unfortunately, integrating and analyzing complex sequence annotations remains logistically challenging. Here we present SHEPHARD, a software package that makes large-scale integrative protein bioinformatics trivial. SHEPHARD is provided as a stand-alone package and with a pre-compiled set of human annotations in a Google Colab notebook.

Five OXA-48-producing Klebsiella pneumoniae were detected in a tertiary referral hospital in Ireland between March and June 2011. They were found in the clinical isolates of five cases that were inpatients on general surgical wards. None of the cases had received healthcare at a facility outside of Ireland in the previous 12 months. This is the first report of OXA-48-producing K. pneumoniae in Ireland.

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Motivation The emergence of high-throughput experiments and high-resolution computational predictions has led to an explosion in the quality and volume of protein sequence annotations at proteomic scales. Unfortunately, sanity checking, integrating, and analyzing complex sequence annotations remains logistically challenging and introduces a major barrier to entry for even superficial integrative bioinformatics. Results To address this technical burden, we have developed SHEPHARD, a Python framework that trivializes large-scale integrative protein bioinformatics. SHEPHARD combines an object-oriented hierarchical data structure with database-like features, enabling programmatic annotation, integration, and analysis of complex datatypes. Importantly SHEPHARD is easy to use and enables a Pythonic interrogation of largescale protein datasets with millions of unique annotations. We use SHEPHARD to examine three orthogonal proteome-wide questions relating protein sequence to molecular function, illustrating its ability to uncover novel biology. Availability We provided SHEPHARD as both a stand-alone software package (https://github.com/holehouse-lab/shephard), and as a Google Colab notebook with a collection of precomputed proteome-wide annotations (https://github.com/holehouse-lab/shephard-colab) Supplementary information Supplementary data are available at Bioinformatics online.