Jerome Kelleher

@jeromekelleher

Python - Algorithms - Bioinformatics. He/him.

Vrijeme pridruživanja: prosinac 2013.

Medijski sadržaj

  1. 23. sij

    Ok, let's do this and everyone else who has contributed. Time to start getting ready for 1.0!

  2. 23. sij

    Great talk from this morning with a nice simple take home message:

  3. 2. sij

    All you have to do is choose stuff from our "catalog": species, chromosome, genetic map and demographic model. Defaults are sensible if you don't care about particular details. Everything is linked back to the original citations if you want to dig deeper.

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  4. 8. stu 2019.

    Hi , I love your project, but please be more clear on the scope of the project, and *please* stop using the politically charged term "British Isles". This image suggests you are only interested in species from the UK (which is absurd):

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  5. 6. lis 2019.

    Coffee time at PopSim! Great discussions so far on what's been achieved in the last year.

  6. 19. ruj 2019.

    ”Binder is the reward you get for software best practices”. leads a workshop on deploying your own binderhub at

  7. 17. ruj 2019.

    Summary: to make software first class we need to

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  8. 2. ruj 2019.

    We also looked at fine-scale population structure within UK Biobank. Even the relatively crude estimated trees and statistics that we have today show population structure at unprecedented resolution. We expect the trees, and methods to analyse them, to improve rapidly.

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  9. 2. ruj 2019.

    We applied tsinfer to large human datasets, and demonstrate that the trees we infer are rich in biological signal. Here we characterise global structure across SGDP and 1000G; structure within the Peruvian 1000G population; and ancestry in one admixed individual.

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  10. 2. ruj 2019.

    Because of the efficiency of tree sequence algorithms, tsinfer scales to millions of whole chromosomes---something like four orders of magnitude larger than previously possible. Despite this enormous leap in efficiency, it's roughly as accurate as the state-of-the-art.

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  11. 2. ruj 2019.

    Our method, tsinfer, works by estimating ancestral haplotypes and using the Li and Stephens model to estimate how ancestors and samples relate to each other. The tree sequence makes this process logically straightforward and highly efficient (our LS implementation is O(log N)).

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  12. 2. ruj 2019.

    But the "succinct tree sequence" (or tree sequence) has changed this. Using this simple encoding we can potentially store the complete genetic history of entire populations on a present-day laptop. Far from being unwieldy, tree sequences can massively compress genetic data.

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  13. 26. srp 2019.

    If you're working with large-scale numerical data, 's talk on zarr from SciPy 2019 is essential viewing: We use zarr internally in tsinfer, and it's superb.

  14. 28. lip 2019.

    Wow! gives us a masterclass in using Dask and other high performance Python tools . These new tools are astonishing!

  15. 26. lip 2019.

    Wrapping up a great talk on with some of linear algebra on the board. Thanks for visiting the BDI !

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  16. 24. lip 2019.

    Love the crafted logo from at the away day. Yan is a man of many talents!

  17. 24. lip 2019.

    Impressive crafting skills at the away day!

  18. 19. lip 2019.

    The final practical session at . takes us through a hybrid forward and coalescent simulation.

  19. 18. lip 2019.

    Cool: 56 active users for the gIMble work-along demo!

  20. 18. lip 2019.

    Live work-along demo of block processing in gIMble from Dom Laetsch.

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