Patrick Gibbs

Patrick Gibbs

@patrickgibbs.bsky.social

PhD Student at Cambridge University. Interested in Quantitative Genetics. Supervised by Xilin Jiang

68 followers102 following14 posts

Patrick Gibbs
@patrickgibbs.bsky.social

Happy to share new manuscript I completed with @ee-reh-neh.bsky.social & @davisjmcc.bsky.social back in Melbourne. The work originally conceived by @ijbeasley.bsky.social focuses on how we can reconcile and meta-analyse eQTL studies across studies cohorts and ancestries. doi.org/10.64898/202...

doi.orgPower is a major confounder in the analysis of cross-ancestry 'portability' in human eQTLsThe phenotypic effects of germline variants are often mediated through gene regulation. Expression quantitative trait loci (eQTLs) are genetic variants associated with changes in gene expression. Understanding how eQTLs vary across populations is essential for characterising the genetic and regulatory drivers of trait diversity. Meta-analysing eQTL studies from multiple populations enables more robust detection of eQTLs and can reveal regulatory mechanisms shaped by population-specific environmental or ancestry-related factors. However, across the multi-ancestry eQTL literature, a wide range of methods have been used to quantify eQTL portability across ancestry groups. Because different studies employ different portability metrics, it is challenging to form a coherent view of the regulatory landscape across populations. In this work, we analyse eQTL summary statistics from ten datasets matched on tissue type and sequencing technology. We compare portability metrics used previously and show that they can yield markedly different patterns of apparent regulatory conservation or divergence. We then examine the statistical determinants of portability across metrics and demonstrate that sample size, minor allele frequency, and linkage disequilibrium are major drivers of the observed differences in eQTL portability across studies. These findings highlight that differences in statistical power stemming from factors such as population size and allele frequency must be accounted for when evaluating eQTL portability. To address this issue, we introduce a new approach designed to correct for these factors when calling eQTL portability. Finally, we show that empirical Bayes multivariate adaptive shrinkage provides a powerful framework for meta-analysing multiple eQTL studies, with the ability to pool signals across populations to produce more robust effect-size estimates within each population. ### Competing Interest Statement The authors have declared no competing interest. National Health and Medical Research Council, https://ror.org/011kf5r70, Ideas Grant 2020501, Investigator Grant 1195595
Irene Gallego Romero@ee-reh-neh.bsky.social

Finally, today's offering! www.biorxiv.org/content/10.6... This began life as a very different project which failed because we couldn't agree on defining eqtl sharing across cohorts. So two young members of the lab dug deeply into this - first @ijbeasley.bsky.social, then @patrickgibbs.bsky.social

biorxiv.orgbiorxiv.org

Patrick Gibbs reposted

Irene Gallego Romero
@ee-reh-neh.bsky.social

Hi yes I will have more to say about this in a few hours but please enjoy this paper. It's been a huge labour of love and effort for the last four years, and a significant part of our research efforts, and I'm so so so thrilled it's finally ready to share. Tldr: scRNA-seq in Indonesia hard but fun

bioRxiv Genomics@biorxiv-genomic.bsky.social

Ancestral and environmental diversity shape the immune landscape in Indonesia https://www.biorxiv.org/content/10.64898/2026.02.15.704933v1

Patrick Gibbs
@patrickgibbs.bsky.social

I cannot recommend Davis’s group more highly! In addition to excellent research, he has been a great mentor!

Davis McCarthy@davisjmcc.bsky.social

📢 PostDoc opportunity in our Bioinformatics & Cellular Genomics lab at SVI! 🧬 You’d join a welcoming, supportive, and brilliant team. Why not spend a few years in Melbourne and be part of something exciting? Apply here: www.seek.com.au/job/84737876 #ScienceCareers #PostDoc #Bioinformatics

seek.com.auResearch Officer - Bioinformatics Job in Fitzroy, Melbourne VIC - SEEKSeeking a Postdoc to develop computational toolkits to enable large-scale studies of single-cell and spatial 'omics and statistical genetics

Patrick Gibbs reposted

Davis McCarthy
@davisjmcc.bsky.social

📢 PostDoc opportunity in our Bioinformatics & Cellular Genomics lab at SVI! 🧬 You’d join a welcoming, supportive, and brilliant team. Why not spend a few years in Melbourne and be part of something exciting? Apply here: www.seek.com.au/job/84737876 #ScienceCareers #PostDoc #Bioinformatics

seek.com.auResearch Officer - Bioinformatics Job in Fitzroy, Melbourne VIC - SEEKSeeking a Postdoc to develop computational toolkits to enable large-scale studies of single-cell and spatial 'omics and statistical genetics

Patrick Gibbs reposted

Carl Zimmer
@carlzimmer.com

The FT reports OpenAI suspects DeepSeek of "a potential breach of intellectual property." As a columnist for NYT, which is suing OpenAI for copyright infringement, and the author of nine books OpenAI apparently used to train its model, I couldn't possibly comment. www.ft.com/content/a0df...

ft.comOpenAI says it has evidence China’s DeepSeek used its model to train competitorWhite House AI tsar David Sacks raises possibility of alleged intellectual property theft
Patrick Gibbs
@patrickgibbs.bsky.social

Very happy to share my first paper! Here we take a look at different models for producing genomic prediction across a wide range of traits. We find that very specific conditions of where ML approaches can out preform linear regression.

Adaptive Evolution Lab@adaevo.bsky.social

📣 New Paper out!!! 📣 When is ML outperforming good old parametric regression for genomic predictions? Go check 👇 doi.org/10.1093/gene...

doi.orgTrait genetic architecture and population structure determine model selection for genomic prediction in natural Arabidopsis thaliana populationsAbstract. Genomic prediction applies to any agro- or ecologically relevant traits, with distinct ontologies and genetic architectures. Selecting the most a
Patrick Gibbs
@patrickgibbs.bsky.social

Molecular traits on the other hand are more neutral (because selection acts on the organism), thus are less confounded by population structure, which we believe further enhances ML prediction, because it allows the effect of distinct markers to be independent across populations.

Patrick Gibbs
@patrickgibbs.bsky.social

Very happy to share my first paper! Here we take a look at different models for producing genomic prediction across a wide range of traits. We find that very specific conditions of where ML approaches can out preform linear regression.

Adaptive Evolution Lab@adaevo.bsky.social

📣 New Paper out!!! 📣 When is ML outperforming good old parametric regression for genomic predictions? Go check 👇 doi.org/10.1093/gene...

doi.orgTrait genetic architecture and population structure determine model selection for genomic prediction in natural Arabidopsis thaliana populationsAbstract. Genomic prediction applies to any agro- or ecologically relevant traits, with distinct ontologies and genetic architectures. Selecting the most a
Patrick Gibbs
@patrickgibbs.bsky.social

Another interesting insight we make is the effect of ancestral selection on genomic predictions. We show how selection acts more strongly on complex traits, (like flowing time) causing variance in the phenotype to be collinear with population structure, which confounds genomic prediction

Patrick Gibbs
@patrickgibbs.bsky.social

Very happy to share my first paper! Here we take a look at different models for producing genomic prediction across a wide range of traits. We find that very specific conditions of where ML approaches can out preform linear regression.

Adaptive Evolution Lab@adaevo.bsky.social

📣 New Paper out!!! 📣 When is ML outperforming good old parametric regression for genomic predictions? Go check 👇 doi.org/10.1093/gene...

doi.orgTrait genetic architecture and population structure determine model selection for genomic prediction in natural Arabidopsis thaliana populationsAbstract. Genomic prediction applies to any agro- or ecologically relevant traits, with distinct ontologies and genetic architectures. Selecting the most a
Patrick Gibbs
@patrickgibbs.bsky.social

We find that ML applications best suit molecular traits. These traits tend to have simpler genetic architectures. We argue that with limited of observations, epistasis is more easily modelled when the variance in a trait is controlled by a few (e.g. 10) SNPs.

Patrick Gibbs
@patrickgibbs.bsky.social

Earlier this year, I was nominated and funded by unimelb to attend the Heidelberg Laureate forum in Germany. The conference connects 200 developing researchers from maths and compsci to award winning scientists inc. winners of the Fields Medal and Turing award. It was an absolute blast!

Patrick Gibbs
@patrickgibbs.bsky.social

Photos: 1. Media training 2. All of the Australians in attendance (I think we were the most represented nation per-capita) 3: Me and my friend Nikil outside the Heidelberg castle 4: Pat Hanrahan and some more friends

Patrick Gibbs
@patrickgibbs.bsky.social

Earlier this year, I was nominated and funded by unimelb to attend the Heidelberg Laureate forum in Germany. The conference connects 200 developing researchers from maths and compsci to award winning scientists inc. winners of the Fields Medal and Turing award. It was an absolute blast!

Patrick Gibbs
@patrickgibbs.bsky.social

There were also opportunities to develop research adjacent skills inc. a media training workshop. I also presented an artistic representation of my research as apart of the “intercultural art project” that runs each year as apart of the conference. I highly recommend the conference!

Patrick Gibbs
@patrickgibbs.bsky.social

Earlier this year, I was nominated and funded by unimelb to attend the Heidelberg Laureate forum in Germany. The conference connects 200 developing researchers from maths and compsci to award winning scientists inc. winners of the Fields Medal and Turing award. It was an absolute blast!

Patrick Gibbs
@patrickgibbs.bsky.social

It was amazing to also meet the other young researchers – every one there had something to teach me, and I learned about all sorts of fields from maths and compsci. I hope to stay in touch with the friends I made there!

Patrick Gibbs reposted

Carl Zimmer
@carlzimmer.com

Over 30 prominent scientists call for a ban on the creation of a "mirror cell"--a microbe made of molecules that are mirror images of their natural forms. It could cause a mind-boggling global disaster. Here's my story [gift link] 🧪https://nyti.ms/3OUCXp6

nyti.msA ‘Second Tree of Life’ Could Wreak Havoc, Scientists Warn (Gift Article)Research on so-called mirror cells, which defy fundamental properties of living organisms, should be prohibited as too dangerous, biologists said.

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