KB Choi

Scientist in Computational Genomics, developing novel computational methods for high-throughput omics data. All views are my own.

[Rafael Irizarry @rafalab]

This UMAP plot was generated from data simulated without inherent clusters, meaning the observed clusters are artifacts.

It highlights how default Seurat clustering and UMAP settings can sometimes produce misleading patterns in data visualization.

[Raimondi Ivan @raimondi_ivan]

🧬 We’re excited to introduce D&D-seq, a single-cell technology that maps DNA:Protein interactions through molecular footprinting.. Check it out here: https://t.co/mfsDO3kKa0 #Genomics #Epigenetics

[KB Choi @kwangbom]

@JeffreyRMillman Congrats Jeff!

[Stephanie Hicks, PhD @stephaniehicks]

Fantastic thread here from @Jess_Osterhout on building a brand as a scientist! If helpful, I wrote some of my thoughts on this important topic a few years back. 😊

https://t.co/jp1hfQKE2M

[KB Choi @kwangbom]

@UNCBBSP @mikelove @UNC_GMB @uncbiostat Congratulations Mike!

[David Beniaguev @DavidBeniaguev]

Out work about "Single Cortical Neurons as Deep Artificial Neural Networks" was finally published in Neuron

With @mikilon and @Segev_Lab

@NeuroCellPress paper: https://t.co/XOrRxVVEjO
code: https://t.co/IGH8DmCucr
data: https://t.co/QswJsD5zfV

All new results in thread below

[𝕐 @nomad421]

Oarfish: Enhanced probabilistic modeling leads to improved accuracy in long read transcriptome quantification https://t.co/UNMtj5jD0P

[𝕐 @nomad421]

Do you do RNA seq quantification with long reads? Well, the COMBINE-lab has something cooking that you might be interested in trying out!

#RNAseq #quantification #transcriptomics

https://t.co/Eg8ZoOT6RL

[Jay Shendure @JShendure]

Our latest out today in @Nature. We profiled 12 million single cells from mouse embryos spanning gastrulation to birth, defined cell type tree from zygote to birth, and unexpectedly found crazy fast changes within first hour of extrauterine life. OA PDF: https://t.co/7PsCcqaQS8

[KB Choi @kwangbom]

@DrMingyaoLi @NatureBiotech @10xGenomics Congrats Mingyao!

[KB Choi @kwangbom]

@k3yavi @nygenome @TheWistar All the best Avi! Keep in touch.

[KB Choi @kwangbom]

I need to try this right now

[Graham Heimberg @gheimberg]

Ever analyze a scRNAseq dataset and wonder if a specific cell state has been seen before? And if so, where in the human body? Under what conditions? Well, now you can use our lightning fast SCimilarity search and foundational model for that! ⚡️🔎🧬 https://t.co/t8L1xFOffd (1/11)

[KB Choi @kwangbom]

It might be interesting to see erosion of XCI/XCR in iPSCs derived from genotyped donors using this new method.

[Luca Pinello @lucapinello]

1/6 A little thread to celebrate this milestone! Our SIMBA manuscript has finally seen the light of day, after a journey of more than 2 years. It's been an intense ride, but we're thrilled with the result.

[Ali Max Erturk @erturklab]

Want to use deep learning for image analysis but lack the coding skills? We introduce DELiVR, a game-changer in brain-wide cell analysis. No coding required, our Fiji Plug-in does the magic. Hats off to @Dorie00, @Rami96614090, @moritz_negwer! 🧵👇🏼 1/n https://t.co/pl7Hwvo2sp

[Ewan Birney @ewanbirney]

It was a tour de force just generating a draft human pan-genome @HumanPangenome, but some suspected and some utterly bizarre things about the human genome have been revealed using these 47 different human reference quality genomes.

[KB Choi @kwangbom]

@Cnspracklen @vishalsarsani Small world. Vishal worked with us at the Jackson Lab before he moved on to his pursuit on doctoral degree.

[Adam Phillippy @aphillippy]

My favorite T2T/Pangenome discovery so far: a multi-megabase inverted segmental duplication on the short arm of chr14 that explains the mechanism of Robertsonian translocations. Great writeup by @ScienceStowers "Answering a 50-year-old mystery" https://t.co/u90TGUwnYt

[Michael Love @mikelove]

This is a really well done python reimplementation of DESeq2 and apeglm, I’ve checked the code closely. Nice work @BorisMuzc @Kramarek et al

[biohub @biohub]

We’re excited to announce 20 new Data Insights grantees addressing challenges in #SingleCell biology by:
🔹Integrating data sets to understand cell functions that regulate health + disease
🔹Applying #ML methods to the analysis of complex data sets
https://t.co/kXZMQ5jB2T