Zuckerberg finances: Building tools for Science Together
The origin of joint computing tools for Human Cell Atlas
Specialist in Computational Statistics Kim-Anh La Cao, working with CZ Biohub scientist Angela Pisco.
Cells are the fundamental units of life, but we still have much to learn about their basic function and organization. There are thousands of cell types and trillions of individual cells working in complex systems to provide a variety of functions in our body, from the immune system to the brain. New experimental technologies for characterization of individual cells - in combination with correct computational approaches - can help us to comprehend this complexity and begin to organize it.
Human Cell Atlas (HCA) is an ambitious global collaboration for creating an open reference map all cells in the human body through a comprehensive description of cell types, their number and spatial locations. Once completed, it will be a fundamental resource for scientists, allowing them to better understand how healthy cells work, and what happens to them wrong when the disease strikes. But assembling, integrating, analyzing and sharing this resource requires a new cloud data infrastructure and new analytical methods for processing and interpreting large and complex different data sets.
CZI supports Human Cell Atlas through the provision of grants, data infrastructure, joint development of open source software and support for collaborative research. As part of this effort, CZI Science recently organized a four-day conference of more than 200 scientists, computer biologists and software engineers to start the creation of joint computing tools for Human Cell Atlas - a series of 85 grants for researchers aimed at working together to solve computational problems for HCA.
cell state, cell type, images, multiomics, trajectories, diversity adjustment, abundance variations, potential spaces, compression, scale, ports and Bioconductor . Some of these groups were actually applied together - others met each other for the first time.
We asked each group to present their work as a whole so that we had 12 group presentations, and not 85 individual projects, and we had lively teleconferences to prepare for the speeches before the meeting. This relaxed organization and teleconferences before the meeting helped to defuse the situation when people arrived. We also developed meeting website with links to repositories, slides, documents and other projects that were merged into the online center during the meeting.
On the first day, 12 groups presented their projects. After these 12 presentations, the groups then spent the next two and a half days working together to better "divide" the work they could do in one year (the duration of the project), attaching special importance to connecting threads, such as common metrics and control Data sets for determining the relative success of different algorithms, data standards and metadata standards, or integration with various ecosystem programming tools. To add some structuring, we also presented four parallel training sessions that will help teach a whole range of topics and inform about them: tools for modern web-based data visualization, a data coordination platform for Human Cell Atlas , using and improving bioRxiv for computational biology and co-programming with Github .
We allocated a lot of time at the meeting so that the groups could work from the time allocated for joint programming, ending with a massive brainstorming session, diluted with presentations from the guests about the current large experimental and computational costs associated with HCA - including inspiring basic information from Dana Peer, leader of the HCA computing community.
The meeting ended with presentations of listeners about what they did and how to continue working together. We left a lot of unplanned time, both for work and for social interaction, to promote open discussion and building relationships. The choice of a venue that would provide participants with both meeting space and accommodation helped in the creation of a community. The supervisory control datasets in Github can last a year, but the smoke and karaoke on the beach is a link that can last throughout the scientific career.
Continuation of the discussion with the fire on the ocean.
Thank you @cziscience for an amazing meeting. It was the most productive, collective and inspiring meeting I attended throughout my career!
- Duygu @ duyguucar
What we have learned is
The three aspects of the meeting were particularly inspiring. First, the groups were really happy to cooperate in providing time, space and tools. Secondly, students and fellow scientists along with PI energized the meeting and probably helped to make sure that the work was indeed done! Thirdly, the introduction of several computing biologists and CZI software engineers helped to facilitate cooperation at the meeting - our team learned a lot from the grantees about problems on the ground, and also helped create cross-sectoral computing capabilities and cooperation.
Everyone was involved in this new assembly structure in their own way: in the best cases, the groups explained the vision and scope of their projects, sometimes literally overseeing or identifying control sets or writing a prototype code. We were also impressed by the groups that found concrete opportunities to participate in a joint collaboration with CZI with open source: Josh Moore from project OMERO Now it works with the command. Starfish over data formats for image-based transcriptomics, and Ryan Williams and Cotton Seed from the scaling group develop more scalable approaches for storing and computing matrices in the Data Coordination Platform.
We were also delighted that the developers of the three key software packages for single-core analysis - Scanpy , Seurat and Scater - have made progress in improving the interoperability of their tools and data formats. Simply being in one room, and having time and support it is possible to stimulate progress.
Chan Zuckerberg Science does amazing things for science.
But working with them was also amazing in terms of culture. This led to scientific discussions with other female experts in the field of computing my age (the first for me!). This helped to create links with different areas, program projects, disciplines. Bravo!
- Anne Carpenter
It was really cool to see that this community brought together a community of HCA computing specialists. As one of the participants told one of us, he felt like a "wood fuel of computing science", and we could not disagree. We are pleased that CZI Science has been able to help initiate such exciting interactions, and we hope to use this meeting as a model, as we continue to run more and more projects.
To learn more about the work in science, please visit our website or subscribe to us on Twitter . To learn more about our technological team, subscribe to the technology blog CZI . To remain aware of the possibilities of financing, subscribe to our newsletter . And you can always contact us at [email protected]
Jeremy Freeman, director, specialist in computational biology
Jeremy is a scientist working with the intersection of biology and engineering. He wants to understand how biological systems work, and use this understanding in the interests of both human health and the design of intelligent systems. He studied computer vision at a magistracy at New York University, headed the neuroscience research laboratory at the Janelia Research Campus HHMI and is currently in the Chan Zuckerberg Initiative, leading our work on areas where computing and biology intersect. He is fond of open source and open science, and also unites scientists and engineers in a number of ways.
Arne Bakker, manager, dealing with scientific meetings and reviews
Arne Bakker is the head of scientific meetings in the scientific group of the Chan Zuckerberg Initiative. He has a doctorate in the field of tumor immunology from the Netherlands Cancer Institute, as well as his research at the University of California at Berkeley. Most recently, Arne was an assistant dean for labor training for masters and beginning scientists in the title of Doctor of Science at Stanford University. Throughout his career, Arne has actively attracted scientists: he was the director of the Discovery Festival in Amsterdam, co-organized Beyond Academia at the University of California at Berkeley and PhD Pathways at Stanford, and volunteered to the Gulf Science Science Festival. In CZI, Arne combines the lessons he has learned from this multi-faceted career to lead our efforts to unite scientists through meetings, seminars and other meetings with the goal of creating and supporting joint scientific communities.
Translation: Diana Sheremyova
About #philtech [/b]
#philtech (technology + philanthropy) Are open publicly described technologies that equalize the standard of living of the greatest possible number of people by creating transparent platforms for interaction and access to data and knowledge. And satisfying the principles of Filtech:
1. Open and copied, not competitive-proprietary.
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3. Sustainable and perspective-oriented, rather than pursuing local benefits.
4. Built on[открытых]data, rather than traditions and beliefs
5. Nonviolent and non-manipulative.
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