Louise Huuki-Myers
lahuuki.bsky.social
Louise Huuki-Myers
@lahuuki.bsky.social
Staff Scientist at LIBD studying brain transcriptomics with #RStats 🧠
PhD Student in Neuroscience at University of Cambridge
lahuuki.github.io
Thanks to @nataliematosin.bsky.social and Sophie Debs for highlighting our work in their editorial “Unlocking the Molecular Secrets of the Human Habenula”
🔗 doi.org/10.1176/appi...
Unlocking the Molecular Secrets of the Human Habenula | American Journal of Psychiatry
PsychiatryOnline.org is the platform for all American Psychiatric Association Publishing journals, DSM, and bestselling textbooks, as well as APA Practice Guidelines, and continuing medical education.
doi.org
November 4, 2025 at 9:31 PM
This data provides a foundation for future work into molecular changes that occur in the #Habenula in disease 🧠🧬 Keep an eye on @lieberinstitute.bsky.social for future work on the Hb spatially resolved transcriptomics with @10xgenomics.bsky.social tech #Visium and #Xenium 👀 #HabenulaLIBD
November 4, 2025 at 9:31 PM
Our #Habenula #singlecell and differential expression data is available to explore via our interactive websites 💻 #opendata github.com/LieberInstit...
GitHub - LieberInstitute/Habenula_Pilot: habenulaPilot project code repository
habenulaPilot project code repository. Contribute to LieberInstitute/Habenula_Pilot development by creating an account on GitHub.
github.com
November 4, 2025 at 9:31 PM
We used #eQTL analysis to examine how SNPs relate to gene expression in #Habenula, 7 eQTLS genes were identified in differential expression, and 16 eSNPs were schizophrenia GWAS risk SNPs. Nine new schizophrenia colocalized genes with genetic risk were identified
November 4, 2025 at 9:31 PM
We investigated whether the DEGs we found were unique to the #Habenula vs. other brain regions studied in schizophrenia (Caudate, Dentate Gyrus, dlPFC, Hippocampus) and found 75% of our DEGs were unique to habenula 🦄
November 4, 2025 at 9:31 PM
Differential gene expression yielded 173 differentially expressed genes between schizophrenia and control donors, some of which support the neurodevelopmental hypothesis of schizophrenia 🌋
November 4, 2025 at 9:31 PM
To refine habenula signal from neighboring thalamus we utilized our #snRNAseq data to perform #deconvolution on our bulk samples, estimating proportion of habenula. These proportions were used to control for dissection differences in the differential expression analysis
November 4, 2025 at 9:31 PM
We also profiled habenula-enriched tissue from schizophrenia and control donors using bulk RNA-seq #Transcriptomics, generating a unique dataset to identify disease associated molecular changes. PCA with bulk data from other regions shows #Habenula as an outlier
November 4, 2025 at 9:31 PM
To provide cross-species context we integrated our human Hb snRNA-seq dataset with a previously published mouse #Habenula #singlecell dataset from @gstuber.bsky.social. Some neuronal subclusters such as human OPRM1-enriched LHb.2 appeared to be conserved across species 🐁
November 4, 2025 at 9:31 PM
Single molecule fluorescence in situ hybridization #RNAScope and HALO from @indicalabs.bsky.social was used to visualize the spatial organization of these human Hb neuronal populations. 🔬 For example, MHb.2 neurons that highly expressed CHAT clustered separately from other MHb cell types
November 4, 2025 at 9:31 PM
We’ve created a #snRNAseq molecular atlas of the human Habenula to understand neuronal diversity on a molecular level in this unique brain region. Our snRNA-seq data on 7 control donors yielded 16k nuclei and 17 clusters, including 7 lateral & 3 medial Hb neuron populations 🧪
November 4, 2025 at 9:31 PM
Thank you to all of our collaborators at the @lieberinstitute.bsky.social for their dedication and hard work on this project! 🧑‍🔬 #HabenulaLIBD @freneegf.bsky.social @nick-eagles.bsky.social @lcolladotor.bsky.social @kr-maynard.bsky.social @martinowk.bsky.social
November 4, 2025 at 9:31 PM
This paper was an exciting culmination of a lots of exploration with #deconvolution ! Check-out my blog post on this work for the TL;DR version: lahuuki.github.io/posts/2025-0...
Deconvolution Benchmark: TL;DR – Louise A. Huuki-Myers
A high level overview of the Deconvolution Benchmark project, now published in Genome Biology!
lahuuki.github.io
April 11, 2025 at 2:35 PM
We also propose and evaluate a new method for selecting cell type specific #markergenes for deconvolution: #MeanRatio implemented in #DeconvoBuddies
@bioconductor.bsky.social #rstats
🛠️ research.libd.org/DeconvoBuddi...
April 11, 2025 at 2:35 PM
To assess method accuracy, we compared the estimated proportions to the #RNAScope proportions for correlations and rmse 📈 #BisqueRNA and #hspe were the top performers 🏆
April 11, 2025 at 2:35 PM
We ran #deconvolution on the 110 bulk RNA-seq samples, with six selected methods: #DWLS, #bisqueRNA, #MuSiC, #BayesPrism, #hspe, and #CIBERSORTx. The methods returned a wide range of proportion estimates 📊
April 11, 2025 at 2:35 PM
The resulting cell type proportions had a large range across the different #DLPFC samples, and were not always correlated with the paired #snRNAseq proportions ⚠️
April 11, 2025 at 2:35 PM
We designed an #RNAScope/IF experiment to measure six broad cell types in the #DLPFC. We used #HALO from Indica Labs to count the occurrence of the cell types across the tissue sections 🔬 #ImmunoFlourescence (awesome work from Kelsey Montgomery)
April 11, 2025 at 2:35 PM
Testing these #deconvolution methods was made possible by a really cool multi-assay dataset from consecutive slices of #DLPFC tissue blocks 🧠1. Bulk RNA-seq 🧬 2. #snRNAseq as the reference 🦠 3. #RNAScope serving as a orthogonal measurement of cell type proportions 🔬
April 11, 2025 at 2:35 PM