The influence of career histories on team perfomance in new product development: a study of the video game industry

The purpose of this research is to contribute to the literature on organizational demography and new product development by investigating how diverse individual career histories impact team performance. Moreover we highlighted the importance of considering also the institutional context and the specific labour market arrangements in which a team is embedded, in order to interpret correctly the effect of career-related diversity measures on performance. The empirical setting of the study is the videogame industry, and the teams in charge of the development of new game titles. Video games development teams are the ideal setting to investigate the influence of career histories on team performance, since the development of videogames is performed by multidisciplinary teams composed by specialists with a wide variety of technical and artistic backgrounds, who execute a significant amounts of creative thinking. We investigate our research question both with quantitative methods and with a case study on the Japanese videogame industry: one of the most innovative in this sector. Our results show how career histories in terms of occupational diversity, prior functional diversity and prior product diversity, usually have a positive influence on team performance. However, when the moderating effect of the institutional setting is taken in to account, career diversity has different or even opposite effect on team performance, according to the specific national context in which a team operates.

Integrating structural variant calling, annotation and prioritization into whole genome analysis workflows: a practical application in the molecular diagnosis of neurodevelopmental disorders

Background: WGS is increasingly used as a first-line diagnostic test for patients with rare genetic diseases such as neurodevelopmental disorders (NDD). Clinical applications require a robust infrastructure to support processing, storage and analysis of WGS data. The identification and interpretation of SVs from WGS data also needs to be improved. Finally, there is a need for a prioritization system that enables downstream clinical analysis and facilitates data interpretation. Here, we present the results of a clinical application of WGS in a cohort of patients with NDD. Methods: We developed highly portable workflows for processing WGS data, including alignment, quality control, and variant calling of SNVs and SVs. A benchmark analysis of state-of-the-art SV detection tools was performed to select the most accurate combination for SV calling. A gene-based prioritization system was also implemented to support variant interpretation. Results: Using a benchmark analysis, we selected the most accurate combination of tools to improve SV detection from WGS data and build a dedicated pipeline. Our workflows were used to process WGS data from 77 NDD patient-parent families. The prioritization system supported downstream analysis and enabled molecular diagnosis in 32% of patients, 25% of which were SVs and suggested a potential diagnosis in 20% of patients, requiring further investigation to achieve diagnostic certainty. Conclusion: Our data suggest that the integration of SNVs and SVs is a main factor that increases diagnostic yield by WGS and show that the adoption of a dedicated pipeline improves the process of variant detection and interpretation.