In this paper we describe how to efficiently record the entire genetic history of a population in forwards-time, individual-based population genetics simulations with arbitrary breeding models, population structure and demography. This approach dramatically reduces the computational burden of tracking individual genomes by allowing us to simulate only those loci that may affect reproduction (those having non-neutral variants). The genetic history of the population is recorded as a succinct tree sequence as introduced in the software package msprime, on which neutral mutations can be quickly placed afterwards. Recording the results of each breeding event requires storage that grows linearly with time, but there is a great deal of redundancy in this information. We solve this storage problem by providing an algorithm to quickly 'simplify' a tree sequence by removing this irrelevant history for a given set of genomes. By periodically simplifying the history with respect to the extant population, we show that the total storage space required is modest and overall large efficiency gains can be made over classical forward-time simulations. We implement a general-purpose framework for recording and simplifying genealogical data, which can be used to make simulations of any population model more efficient. We modify two popular forwards-time simulation frameworks to use this new approach and observe efficiency gains in large, whole-genome simulations of one to two orders of magnitude. In addition to speed, our method for recording pedigrees has several advantages: (1) All marginal genealogies of the simulated individuals are recorded, rather than just genotypes. (2) A population of N individuals with M polymorphic sites can be stored in O(N log N + M) space, making it feasible to store a simulation's entire final generation as well as its history. (3) A simulation can easily be initialized with a more efficient coalescent simulation of deep history. The software for recording and processing tree sequences is named tskit.

OBJECTIVE: To describe current practices and stakeholder perspectives of patient portals in the acute care setting. We aimed to: (1) identify key features, (2) recognize challenges, (3) understand current practices for design, configuration, and use, and (4) propose new directions for investigation and innovation. MATERIALS AND METHODS: Mixed methods including surveys, interviews, focus groups, and site visits with stakeholders at leading academic medical centers. Thematic analyses to inform development of an explanatory model and recommendations. RESULTS: Site surveys were administered to 5 institutions. Thirty interviews/focus groups were conducted at 4 site visits that included a total of 84 participants. Ten themes regarding content and functionality, engagement and culture, and access and security were identified, from which an explanatory model of current practices was developed. Key features included clinical data, messaging, glossary, patient education, patient personalization and family engagement tools, and tiered displays. Four actionable recommendations were identified by group consensus. DISCUSSION: Design, development, and implementation of acute care patient portals should consider: (1) providing a single integrated experience across care settings, (2) humanizing the patient-clinician relationship via personalization tools, (3) providing equitable access, and (4) creating a clear organizational mission and strategy to achieve outcomes of interest. CONCLUSION: Portals should provide a single integrated experience across the inpatient and ambulatory settings. Core functionality includes tools that facilitate communication, personalize the patient, and deliver education to advance safe, coordinated, and dignified patient-centered care. Our findings can be used to inform a "road map" for future work related to acute care patient portals.

UNLABELLED: A C++ class library is available to facilitate the implementation of software for genomics and sequence polymorphism analysis. The library implements methods for data manipulation and the calculation of several statistics commonly used to analyze SNP data. The object-oriented design of the library is intended to be extensible, allowing users to design custom classes for their own needs. In addition, routines are provided to process samples generated by a widely used coalescent simulation. AVAILABILITY: The source code (in C++) is available from http://www.molpopgen.org