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1. The Secret Life of Hackathon Code Where does it come from and where does it go?

   https://doi.org/10.1109/MSR52588.2021.00020  

   Imam, Ahmed; Dey, Tapajit; Nolte, Alexander; Mockus, Audris; Herbsleb, James D. (May 2021, Mining Software Repositories)

   null (Ed.)

   Background: Hackathons have become popular events for teams to collaborate on projects and develop software prototypes. Most existing research focuses on activities during an event with limited attention to the evolution of the code brought to or created during a hackathon. Aim: We aim to understand the evolution of hackathon-related code, specifically, how much hackathon teams rely on pre-existing code or how much new code they develop during a hackathon. Moreover, we aim to understand if and where that code gets reused, and what factors affect reuse. Method: We collected information about 22,183 hackathon projects from DEVPOST– a hackathon database – and obtained related code (blobs), authors, and project characteristics from the WORLD OF CODE. We investigated if code blobs in hackathon projects were created before, during, or after an event by identifying the original blob creation date and author, and also checked if the original author was a hackathon project member. We tracked code reuse by first identifying all commits containing blobs created during an event before determining all projects that contain those commits. Result: While only approximately 9.14% of the code blobs are created during hackathons, this amount is still significant considering time and member constraints of such events. Approximately a third of these code blobs get reused in other projects. The number of associated technologies and the number of participants in a project increase reuse probability. Conclusion: Our study demonstrates to what extent pre-existing code is used and new code is created during a hackathon and how much of it is reused elsewhere afterwards. Our findings help to better understand code reuse as a phenomenon and the role of hackathons in this context and can serve as a starting point for further studies in this area. 

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2. Meltos: multi-sample tumor phylogeny reconstruction for structural variants

   https://doi.org/10.1093/bioinformatics/btz737  

   Ricketts, Camir; Seidman, Daniel; Popic, Victoria; Hormozdiari, Fereydoun; Batzoglou, Serafim; Hajirasouliha, Iman; Valencia, Alfonso (October 2019, Bioinformatics)

   Abstract Motivation We propose Meltos, a novel computational framework to address the challenging problem of building tumor phylogeny trees using somatic structural variants (SVs) among multiple samples. Meltos leverages the tumor phylogeny tree built on somatic single nucleotide variants (SNVs) to identify high confidence SVs and produce a comprehensive tumor lineage tree, using a novel optimization formulation. While we do not assume the evolutionary progression of SVs is necessarily the same as SNVs, we show that a tumor phylogeny tree using high-quality somatic SNVs can act as a guide for calling and assigning somatic SVs on a tree. Meltos utilizes multiple genomic read signals for potential SV breakpoints in whole genome sequencing data and proposes a probabilistic formulation for estimating variant allele fractions (VAFs) of SV events. Results In order to assess the ability of Meltos to correctly refine SNV trees with SV information, we tested Meltos on two simulated datasets with five genomes in both. We also assessed Meltos on two real cancer datasets. We tested Meltos on multiple samples from a liposarcoma tumor and on a multi-sample breast cancer data (Yates et al., 2015), where the authors provide validated structural variation events together with deep, targeted sequencing for a collection of somatic SNVs. We show Meltos has the ability to place high confidence validated SV calls on a refined tumor phylogeny tree. We also showed the flexibility of Meltos to either estimate VAFs directly from genomic data or to use copy number corrected estimates. Availability and implementation Meltos is available at https://github.com/ih-lab/Meltos. Contact imh2003@med.cornell.edu Supplementary information Supplementary data are available at Bioinformatics online. 

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3. Final Report: FAIR Hackathon Workshop for Mathematical and Physical Sciences Research Communities

   https://doi.org/10.7274/r0-rwpp-as13  

   Hildreth, Michael D; Meyers, Natalie K (January 2020, MPS FAIR Hackathon)

   The FAIR Hackathon Workshop for Mathematics and the Physical Sciences (MPS) February 27-28, 2019 in Alexandria, Virginia brought together forty-four stakeholders in the physical sciences community to share skills, tools and techniques to FAIRify research data. As one of the first efforts of its kind in the US, the workshop offered participants a way to engage with FAIR principles (Findable, Accessible, Interoperable and Reusable) Data and metrics in the context of a hackathon. The workshop was designed to address issues of public access to data and to provide experience with FAIR tools and relevant hands-on experience for researchers. Existing FAIR tools and infrastructure were introduced. Hands-on hackathon breakout time was devoted to testing FAIR metrics and tools against physical sciences data. The hackathon invited MPS research data management stakeholders to react to the FAIR principles and to jointly consider gaps in the MPS data sharing ecosystem in the context of researcher’s actual projects. FAIR Gap analysis was introduced as a way to identify community-specific tools or infrastructure that could dramatically enhance the ability of domain scientists to make their data more FAIR. 

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4. Genomic structural variation: A complex but important driver of human evolution

   https://doi.org/10.1002/ajpa.24713  

   Soto, Daniela C.; Uribe‐Salazar, José M.; Shew, Colin J.; Sekar, Aarthi; McGinty, Sean P.; Dennis, Megan Y. (February 2023, American Journal of Biological Anthropology)

   Abstract Structural variants (SVs)—including duplications, deletions, and inversions of DNA—can have significant genomic and functional impacts but are technically difficult to identify and assay compared with single‐nucleotide variants. With the aid of new genomic technologies, it has become clear that SVs account for significant differences across and within species. This phenomenon is particularly well‐documented for humans and other primates due to the wealth of sequence data available. In great apes, SVs affect a larger number of nucleotides than single‐nucleotide variants, with many identified SVs exhibiting population and species specificity. In this review, we highlight the importance of SVs in human evolution by (1) how they have shaped great ape genomes resulting in sensitized regions associated with traits and diseases, (2) their impact on gene functions and regulation, which subsequently has played a role in natural selection, and (3) the role of gene duplications in human brain evolution. We further discuss how to incorporate SVs in research, including the strengths and limitations of various genomic approaches. Finally, we propose future considerations in integrating existing data and biospecimens with the ever‐expanding SV compendium propelled by biotechnology advancements. 

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5. An integrated peach genome structural variation map uncovers genes associated with fruit traits

   https://doi.org/10.1186/s13059-020-02169-y  

   Guo, Jian; Cao, Ke; Deng, Cecilia; Li, Yong; Zhu, Gengrui; Fang, Weichao; Chen, Changwen; Wang, Xinwei; Wu, Jinlong; Guan, Liping; et al (December 2020, Genome Biology)

   null (Ed.)

   Abstract Background Genome structural variations (SVs) have been associated with key traits in a wide range of agronomically important species; however, SV profiles of peach and their functional impacts remain largely unexplored. Results Here, we present an integrated map of 202,273 SVs from 336 peach genomes. A substantial number of SVs have been selected during peach domestication and improvement, which together affect 2268 genes. Genome-wide association studies of 26 agronomic traits using these SVs identify a number of candidate causal variants. A 9-bp insertion in Prupe.4G186800 , which encodes a NAC transcription factor, is shown to be associated with early fruit maturity, and a 487-bp deletion in the promoter of PpMYB10.1 is associated with flesh color around the stone. In addition, a 1.67 Mb inversion is highly associated with fruit shape, and a gene adjacent to the inversion breakpoint, PpOFP1 , regulates flat shape formation. Conclusions The integrated peach SV map and the identified candidate genes and variants represent valuable resources for future genomic research and breeding in peach. 

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