Hector RdB
@hector_rdb
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PhD student in Biostatistics in Berkeley, triathlete and 'Omics enthusiast
Joined March 2016
Also, be sure to check out Crater Lake in the winter, which provided inspiration for the name of the method (photo credits to @KhalilOuard).
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The code of CALDERA is available on Github: https://t.co/5r7Zfz1yCZ The paper is also on Github. https://t.co/emGkEYyoxa Thanks also to @fannyperraudeau, Michael Souza, Arnaud Mary and @cendrinou for their help in this work!
github.com
Contribute to HectorRDB/Caldera_ISMB development by creating an account on GitHub.
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CALDERA is now out in the proceedings of @ISMBinfo! You can find the paper here https://t.co/RTKNNK4uOI and a thread below by @ljacob explaining the core concepts and results of the paper.
academic.oup.com
AbstractMotivation. Genome-wide association studies (GWAS), aiming to find genetic variants associated with a trait, have widely been used on bacteria to i
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Really nice to have someone a little famous 🤩reporting that our medical 5 strains probiotic, Pendulum Glucose Control, helps her! BMJ paper for safety and BMC for mechanism of action. @Pendulum_Co
instagram.com
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One of my biggest pet peeves: When old historic maps overlap with modern political maps. A 🧵
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Very happy of this work: It combines both fun ideas on graph exploration (such as reverse search) and statistical testing (testability). Check out this thread by @ljacob to understand more or you can find the preprint at
biorxiv.org
Genome wide association studies (GWAS), aiming to find genetic variants associated with a trait, have widely been used on bacteria to identify genetic determinants of drug resistance or hypervirule...
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Come check out our workshop! We’ve made some great improvements since last year. It’s a little late for CEST but coffee and Bourgogne should help me pull through :)
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I'm excited to introduce a preprint describing TreeVAE, a project led by Khalil Ouardini, a fantastic Master's student who spent the past year interning with @_romain_lopez_ and myself in the @YosefLab. Here's the preprint:
biorxiv.org
Novel experimental assays now simultaneously measure lineage relationships and transcriptomic states from single cells, thanks to CRISPR/Cas9-based genome engineering. These multimodal measurements...
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Hi #ml #optimization twitter! Recently @fpedregosa and I have been working on a *constrained* optimization library for PyTorch. https://t.co/3CUtfSrqg4 Why constrained? Scale matters! Adversarial examples are one nice example of this.
github.com
CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training. - openopt/chop
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Open post-doc position at @UCBStatistics, in the groups of @cendrinou and Elizabeth Purdom, on the development of statistical methods and software for single-cell sequencing data. Very highly recommended; these are some of the best mentors you can get! https://t.co/BYLWNuk1NJ
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We presented versions of this work at Bioc2020 and euro Bioc2020 last year. Those workshops are available on youtube if you prefer video to the paper format ( https://t.co/F9tGSKhre3 and https://t.co/3Zjhry28Wy). 5/5
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This all started from a Github issue on the tradeSeq repo ( https://t.co/dCm7LltNaJ), proving once again that open-source software and user feedbacks are truly beneficial for everyone involved. So please use the software, break it, ask questions and open issues!! 4/5
github.com
We have a trajectory of single cells generated by slingshot, but the cells are mixed from two conditions (mutant, wild-type)--in other words, we have one unified slingshot object and one trajectory...
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You can also go check out the package on Github: https://t.co/V3OxEnm0lz. Moreover, the paper is fully reproducible and you can check all the case studies and simulations on GitHub as well: https://t.co/1jrZ7b3ZQd. 3/5
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We break this question into three distinct parts: should we fit a common trajectory? What are the large scale differences between conditions? What are the genes that are driving those changes? This allows for a framework that is both more powerful and more interpretable. 2/5
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Very happy to announce my latest work in collaboration with @koenvdberge_Be @justokstreet and @cendrinou: condiments is a workflow and an R package designed to tackle the question of trajectory inference under multiple conditions. The preprint has is now on Biorxiv. 1/5
Trajectory inference across multiple conditions with condiments: differential topology, progression, differentiation, and expression. https://t.co/ybCzZWyTgX
#bioRxiv
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Thrilled to share that #totalVI (our method for joint analysis of CITE-seq data) is now published in @naturemethods! It has been a fantastic collaboration with @airstreets, @YosefLab, and my co-first author @adamgayoso. Check out the tutorials on https://t.co/WzkQdxmrPC.
scvi-tools.org
Probabilistic models for single-cell omics data
Total Variational Inference is a framework for end-to-end analysis of paired transcriptome and protein measurements such as CITE-seq data in single cells from the Streets and Yosef labs. https://t.co/WjmxpJrtce
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Really enjoyed the workshop by @justokstreet @koenvdberge_Be and @hector_rdb earlier tonight! Really cool work on trajectory analysis! Try it out for yourself at https://t.co/hL9mjvfI8d
#EuroBioc2020
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For our last level 500 workshop, Kelly Street @justokstreet Koen Van den Berge @koenvdberge_Be and Hector Roux de Bezieux @hector_rdb present "Trajectory inference across conditions: differential expression and differential progression" Join the fun! 💯 #BioC2020 #rstats
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