Let’s play a little game. Let’s say that you’re the CSO at a cancer pharma company, and you have to choose a target to go after. Here’s a gene – high expression is associated with poor prognosis in brain cancer. Looks like a good candidate for an inhibitor right?

Welcome Professor Boran Gao! Gao will work in Purdue Biological Sciences and Purdue Statistics Department He develops statistical methods and computational tools to better understand genetic data, with a focus on improving health outcomes for underrepresented populations. #Purdue #PurdueScience #Biology

GWAS is typically run for cross-sectional traits and not longitudinal trait trajectories📈🧬 👉New paper describes an application of linear mixed models for longGWAS of eGFR decline 👉Modeling function of age with random slopes & intercepts was statistically advantageous link👇

Spatial Omics enthusiasts!! Spatial Proteomics is the Method of the Year 2024 🤩🤩🤩 nature.com/nmeth/volumes/…

Single-cell Mendelian randomization (MR) and colocalization using cis-eQTLs from brain snRNAseq🧬❗️ 👉coloc revealed 256 gene–cell-type–trait triplets for brain disease 👉140 of them also supported by MR 👉<40% would be detected with bulk eQTLs

Excited to share our latest work: Celina, a statistical method to identify cell type-specific spatially variable genes in spatial transcriptomics data. Check out the full study here: nature.com/articles/s4146… Xiang Zhou Peijun Wu MD Anderson Cancer Center

I am giving a seminar discussing recent criticism of using UMAP in All of Us paper in Nature doi.org/10.1038/s41586…. I will compare peculiarities of UMAP for single cell biology vs. population genomics applications. Join if you are interested, scilifelab.se/event/is-umap-….

VINTAGE: An alternative framework for transcriptome-wide association studies to detect and decipher gene-trait associations biorxiv.org/content/10.110…

Many settle for pseudo-bulk DE in single-cell genomics due to analysis challenges. If you're aiming for true single-cell resolution, check out our latest report on common pitfalls and a framework to overcome them. link.springer.com/article/10.118…

By modeling cross-ancestry correlations & accounting for LD variations across ancestries, @AJHGNew's latest article demonstrates that CARMA-X results in robust performance when only summary statistics & reference LD matrices are used for inference: cell.com/ajhg/abstract/… #ASHG

Our April issue is live! 🌧️🌷 nature.com/nmeth/volumes/… On the cover, Spotiphy projects scRNA-seq and histological image data onto the spatial transcriptome. Artwork by Jiyuan Yang St. Jude Research. Paper: nature.com/articles/s4159…

A reference panel for linkage disequilibrium and genotype imputation using whole-genome sequencing data from 2,680 participants ... biorxiv.org/content/10.110… #biorxiv_genetic

LoGicAl: Local Ancestry and Genotype Calling Uncertainty-aware Ancestry-specific Allele Frequency Estimation from Admixed Samples biorxiv.org/content/10.110… #biorxiv_genetic

Topological velocity inference from spatial transcriptomic data go.nature.com/4lyR02w