Zach Fuller

@zl_fuller

Population geneticist and postdoc at Columbia with Molly Przeworski. National Geographic Young Explorer

Vrijeme pridruživanja: travanj 2014.

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  1. proslijedio/la je Tweet
    30. sij

    An updated version of our ( and ) work on the factors affecting the performance of polygenic scores--beyond genetic ancestry—is accepted and now up [thread]

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  2. proslijedio/la je Tweet
    23. sij

    Here it is: the first ! Available from ThermoFisher Scientific, data can be analyzed with workflow. Resolves Acropora host genotypes, pops, spp AND symbionts. Comment on

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  3. proslijedio/la je Tweet
    22. sij

    I'm looking for a computational postdoc for analyzing palaeogenomic data, co-advised with , to start around September 2020. Deadline for applying is March 15th. Link here:

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  4. proslijedio/la je Tweet
    20. sij

    Are you graduating soon and interested in the evolution and genetics of complex traits? We looking to hire a post-doc! Drop me a line!

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  5. proslijedio/la je Tweet
    15. sij
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  6. 9. sij

    Thanks to and our Acropora millepora reference panel and imputation pipeline are now publicly available. Let me know if you have data you want to try it on! Here’s some background:

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  7. proslijedio/la je Tweet
    13. pro 2019.

    Extremely excited to share the first major project from our lab, led by the brilliant with major contributions from Mateo Garcia, Mackenzie Keegan, , , , Manfred Schartl, and other co-authors:

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  8. 6. pro 2019.

    We are looking forward to any comments or feedback, please contact me with any questions. Excited for this work to continue in the future and where the next findings take us (23/n)

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  9. 6. pro 2019.

    For those of you who know us, may know Molly and I do not have a background in corals - so besides all of their work in this project, and were incredibly helpful and generous in introducing us into this system and the coral world (22/n)

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  10. 6. pro 2019.

    All co-authors had major contributions to this project, so a sincere thank you to all involved! Also many helpful conversations with other along the way, including and , and for the assembly (21/n)

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  11. 6. pro 2019.

    This was a large undertaking involving many people, so there are many thanks to go around - first of course to (20/n)

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  12. 6. pro 2019.

    We released all the data and provide an extensive supplement that we hope can be helpful for similar genomics based approaches in other non-model organisms (19/n)

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  13. 6. pro 2019.

    Supported by the Agouron Institute, new collections and field work are underway as we speak for led by and (18/n)

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  14. 6. pro 2019.

    As sample sizes increase, so will our prediction accuracy and power to detect associations. Here, we show that such an approach is feasible in A. millepora and we are already taking the next steps towards this end (17/n)

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  15. 6. pro 2019.

    We view this work as an important first step towards incorporating genomics to study traits of conservation importance. While still a massive dataset, ~200 individuals for a GWAS leaves us under powered in the absence of major effect loci (16/n)

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  16. 6. pro 2019.

    However, combining a polygenic score with environmental data and information for the dominant symbiont species, we can explain >60% of the variation in bleaching for our samples (using cross-validation) (15/n)

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  17. 6. pro 2019.

    Through cross-validation, we show that this answer is yes (but a weak yes). While a polygenic score for bleaching gives a significant increase in prediction accuracy, it is a small increase on its own (14/n)

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  18. 6. pro 2019.

    But prior evidence strongly points to bleaching response being partly heritable in the coral, so are the combined estimated effects of variants genome-wide predictive of bleaching? (13/n)

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  19. 6. pro 2019.

    No single SNP reach genome-wide significance, indicating the absence of common, large effect loci underlying variation in bleaching response (12/n)

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  20. 6. pro 2019.

    We then turn our attention to a GWAS for variation in bleaching and to the development of a polygenic score and predictive model (11/n)

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