Guillermo Parada

Common and rare genetic variants show network convergence for a majority of human traits While both common and rare variants contribute to the genetic etiology of complex traits, whether their impacts manifest through the same effector genes and molecular mechanisms is not well understood...

Interesting new @medrxivpreprint.bsky.social study, bearing on the interpretation of GWAS results: 
“Common and rare genetic variants show network convergence for a majority of human traits” 🧪🧬
www.medrxiv.org/content/10.1...

A multimodal conversational agent for DNA, RNA and protein tasks - Nature Machine Intelligence De Almeida, Richard and colleagues leverage transfer learning to create ChatNT, a multimodal conversational agent for DNA, RNA and protein sequences that can be instructed in natural language.

www.nature.com/articles/s42...

Dissecting regulatory syntax in human development with scalable multiomics and deep learning Transcription factors (TFs) establish cell identity during development by binding regulatory DNA in a sequence-specific manner, often promoting local chromatin accessibility, and regulating gene expre...

Delighted to share our latest work deciphering the landscape of chromatin accessibility and modeling the DNA sequence syntax rules underlying gene regulation during human fetal development! www.biorxiv.org/content/10.1... Read on for more: 🧵 1/16 #GeneReg 🧬🖥️

Machine learning (ML) is revolutionizing genomics, but common pitfalls can lead to misleading results. Here's a thread on how to avoid them 🧵

Description of image: Workflow for identifying high-quality ASBs through baal-nf. ChIP-sequencing data from genotyped cell lines is used to infer ASBs at heterozygous SNPs using BaalChIP. Identified ASBs are further characterized by mapping them to JASPAR and NoPeak motifs for a given TF. High-quality ASBs show concordance in the corrected allelic ratio and motif score difference.

What DNA variants alter transcription factor (TF) binding affinity? Here, we describe a new workflow baal-nf. We used it to trawl through 6017 ChIP-Seq data sets for 558 TFs and 46 genotyped cell lines, finding 298,783 allele-specific binding sites (ASBs).
www.biorxiv.org/content/10.1...
1/2

Very excited to announce that the single cell/nuc. RNA/ATAC/multi-ome resource from ENCODE4 is now officially public. This includes raw data, processed data, annotations and pseudobulk products. Covers many human & mouse tissues. 1/

www.encodeproject.org/single-cell/...

Analysis of multi-condition single-cell data with latent embedding multivariate regression - Nature Genetics Latent embedding multivariate regression models multi-condition single-cell RNA-seq using a continuous latent space, enabling data integration, per-cell gene expression prediction and clustering-free ...

How to do differential expression with scRNAseq data? State of the art is "pseudo-bulk" analysis with RNA-seq methods like edgeR or DESeq2, where "cell type" is encoded as discrete categories. Biologically, discrete categories are not always the most appropriate concept.(1/3)
doi.org/10.1038/s415...

New brain aging study is out today in Nature

The largest single-cell RNA seq dataset of mouse brain aging reveals incredible insights and could pave the way for future therapies to slow or manage the impacts of the aging process. 🧵 #studyBRAIN

Method of moments framework for differential expression analysis of single-cell RNA sequencing data: Cell
www.cell.com/cell/fullte...

The most complete collection of uniformly processed ChIP-seq data on identification of transcription factor binding sites for human and mouse. Convenient web interface with advanced search, browsing and genome browser based on the BioUML platform. gtrd.biouml.org/

ChIP-DIP maps binding of hundreds of proteins to DNA simultaneously and identifies diverse gene regulatory elements www.nature.com/articles/s4...

Totally agree, real science is really hard! - So much so, that if you don't have fun while doing it, you may get easily frustrated between the "trial and error circuit"

Real science:
1. Is not correlated with the amount of funding
2. Progresses slowly, usually taking many years
3. Leads to more questions than it answers
4. Advances when we disengage & in improvisational discussions
5. Is too important a thing to be done in a non-playful way

🌟 Thrilled to announce that our project, Deep Immune Receptor Modeling (#DIRM), has been awarded funding under the (@novo-nordisk.bsky.social) Nordisk Foundation Data Science Collaborative Research Programme! 🎉

GenomeDelta: detecting recent transposable element invasions without repeat library - Genome Biology We present GenomeDelta, a novel tool for identifying sample-specific sequences, such as recent transposable element (TE) invasions, without requiring a repeat library. GenomeDelta compares high-qualit...

Our novel tool for finding recent TE invasions without repeat library - great work by amazing student Riccardo (not yet on bsky) genomebiology.biomedcentral.com/articles/10....

We applied Squidiff to model blood vessel #organoids using single-cell RNA sequencing to examine their response to neutron irradiation and pro-regenerative G-CSF treatment, simulating cosmic irradiation anticipated in #deepspace missions🧑‍🚀. 5/🦑

Proud of this work spearheaded by the phenomenal @jlfan.bsky.social and @mingxz.bsky.social in collaboration w/ Ben Izar! The past 3 years we've worked hard to unravel how #CNVs shape #tumor phenotypic plasticity seen in #singlecell #RNAseq data ➡️ #Echidna 🦔

CRISPR-StAR enables high-resolution genetic screening in complex in vivo models - Nature Biotechnology Pooled genetic CRISPR screening is improved in complex models through leveraging internal controls.

Today we published a new paradigm to do CRISPR screens in complex model systems such as in vivo but also e.g. in organoids. The publication came out in Nature Biotechnology.
1/
www.nature.com/articles/s41...

Mis-splicing of a neuronal microexon promotes CPEB4 aggregation in ASD - Nature The molecular mechanisms of how small changes in the degree of inclusion of a neuron-specific microexon in CPEB4 lead to dominant-negative effects in the expression of genes associated with autism spe...

This is huge. Mis-splicing of a 24nt-long micro-exon in the CPEB4 #RNA binding protein leads to formation of irreversible aggregates, which normally would dissolve after depolarization, and consequent deregulation of genes associated with autism spectrum disorders www.nature.com/articles/s41...