The McCarthy lab @davisjmcc.bsky.social is very excited to be in beautiful Adelaide for the 10th ABACBS conference. Look at our happy faces @aaronkwc.bsky.social @ameliadunstone #ABACBS2025
Aaron Kwok
@aaronkwc.bsky.social
PhD student at Bioinformatics and Cellular Genomics group @SVIResearch
Great new work led by Aaron Kwok from @davisjmcc.bsky.social’s group. A tool to “denoise” contaminating transcripts from image based spatial data. www.biorxiv.org/content/10.1...
Denoising image-based spatial transcriptomics data with DenoIST
Image-based spatial transcriptomics (IST) technologies provide unprecedented resolution of gene expression in tissue sections, but suffer from contamination of cells' gene expression profiles due to i...
biorxiv.org
Very excited to share new work from my PhD on a new software package for eQTL mapping: quasar. The quasar software package is a C++ program designed to provide a flexible and efficient eQTL mapping. www.medrxiv.org/content/10.1...
Flexible and efficient count-distribution and mixed-model methods for eQTL mapping with quasar
Identifying genetic variants that affect gene expression, expression quantitative trait loci (eQTLs), is a major focus of modern genomics. Today, various methods exist for eQTL mapping, each using dif...
medrxiv.org
Here it is! Bonsai. Now there is really no more excuse for using t-SNE/UMAP. Bonsai not only makes cool pictures of your data. It actually rigorously preserves its structure. No tunable parameters. Incredible work by @dhdegroot.bsky.social. I'm so excited about this! www.biorxiv.org/content/10.1...
Bonsai: Tree representations for distortion-free visualization and exploratory analysis of single-cell omics data
Single-cell omics methods promise to revolutionize our understanding of gene regulatory processes during cell differentiation, but analysis of such data continues to pose a major challenge. Apart from...
biorxiv.org
Excited to share Ruqian has developed a package for this transcript based niche analysis. Check out the preprint and the package! This is a flexible approach and we're working on extending this for other spatial analyses! @davisjmcc.bsky.social www.biorxiv.org/content/10.1...
SpatialRNA: a python package for easy application of Graph Neural Network models on single-molecule spatial transcriptomics dataset
Image-based spatial transcriptomics deliver gene expression measurements of RNA transcripts in tissue slices with single-molecule resolution and spatial context preserved. Modern Graph Neural Network ...
biorxiv.org
Nick Banovich@nebanovich.bsky.social · 2y agoTo go beyond manual annotations, we computationally identified multicellular spatial “niches” both using Seurat v5 and with a custom, transcript-based approach developed by co-first author @Ruqian_lyu using the GraphSAGE framework.
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...
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 ...
doi.org
Biologist, stop putting UMAP plots in papers! Blogpost here: simplystatistics.org/posts/2024-1...
Simply Statistics: Biologists, stop putting UMAP plots in your papers
UMAP is a powerful tool for exploratory data analysis, but without a clear understanding of how it works, it can easily lead to confusion and misinterpretation.
simplystatistics.org
What do GWAS and rare variant burden tests discover, and why? Do these studies find the most IMPORTANT genes? If not, how DO they rank genes? Here we present a surprising result: these studies actually test for SPECIFICITY! A 🧵on what this means... (🧪🧬) www.biorxiv.org/content/10.1...
Specificity, length, and luck: How genes are prioritized by rare and common variant association studies
Standard genome-wide association studies (GWAS) and rare variant burden tests are essential tools for identifying trait-relevant genes. Although these methods are conceptually similar, we show by anal...
biorxiv.org
Many thanks to my supervisors @davisjmcc.bsky.social and Heejung who encouraged me to write this piece up! It is not a style of writing that I am the most familiar with so it took a lot of experimenting and also valuable feedback from @jeffreypullin.bsky.social on some earlier versions
Davis McCarthy@davisjmcc.bsky.social · 2y agoHave you been thinking hard about statistical modelling of scATAC-seq data? (No.) Luckily for you, @aaronkwc.bsky.social has! Aaron will help you grok: What's going on? What is TF-IDF? Is there really single-cell level chromatin information? Check it out 👇 www.biorxiv.org/content/10.1... 🧪🧬💻
New work! Wherein we (as in, the AVE ODIC working group) looked at clinical variant classification across genetic ancestry groups in gnomAD and AoU and what we found... is exactly what you might expect, after decades of Eurocentric research. But we also show there's a better way forward! 🧬🖥️
medRxivpreprint@medrxivpreprint.bsky.social · 2y agoDefining and Reducing Variant Classification Disparities https://www.medrxiv.org/content/10.1101/2024.04.11.24305690v1
Have you been thinking hard about statistical modelling of scATAC-seq data? (No.) Luckily for you, @aaronkwc.bsky.social has! Aaron will help you grok: What's going on? What is TF-IDF? Is there really single-cell level chromatin information? Check it out 👇 www.biorxiv.org/content/10.1... 🧪🧬💻
Going beyond cell clustering and feature aggregation: Is there single cell level information in single-cell ATAC-seq data?
Single-cell Assay for Transposase Accessible Chromatin with sequencing (scATAC-seq) has become a widely used method for investigating chromatin accessibility at single-cell resolution. However, the re...
biorxiv.org