📢 #TOPMed e/sQTL atlas is out in @science.org today!
Happy to contribute to this amazing team effort and rich resource for the genomics community: 69k cis-eQTL + 35k cis-sQTL across 6 tissues/cell types and diverse ancestries.
Still more to discover 😉🧬
www.science.org/doi/10.1126/...
Happy to contribute to this amazing team effort and rich resource for the genomics community: 69k cis-eQTL + 35k cis-sQTL across 6 tissues/cell types and diverse ancestries.
Still more to discover 😉🧬
www.science.org/doi/10.1126/...
Cross-cohort analysis of expression and splicing quantitative trait loci in TOPMed
Most genetic variants associated with complex traits are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterized 14,324 RNA-sequen...
www.science.org
July 16, 2026 at 10:31 PM
📢 #TOPMed e/sQTL atlas is out in @science.org today!
Happy to contribute to this amazing team effort and rich resource for the genomics community: 69k cis-eQTL + 35k cis-sQTL across 6 tissues/cell types and diverse ancestries.
Still more to discover 😉🧬
www.science.org/doi/10.1126/...
Happy to contribute to this amazing team effort and rich resource for the genomics community: 69k cis-eQTL + 35k cis-sQTL across 6 tissues/cell types and diverse ancestries.
Still more to discover 😉🧬
www.science.org/doi/10.1126/...
An amazing amount of work here eQTL and sQTL with n>14k donors! Bravo.
27% of GWAS signals colocalized only with _secondary_ e/sQTL signals in the locus... important to think about this as we try to understand mechanisms
27% of GWAS signals colocalized only with _secondary_ e/sQTL signals in the locus... important to think about this as we try to understand mechanisms
📢 Thrilled to see this out, an atlas of e/sQTL across multiple tissues and diverse ancestries in 14,324 TOPMed participants: www.medrxiv.org/content/10.1...
Grateful to the #TOPMed #Omics WG for giving me an opportunity to learn and contribute to this important work 🧬
Grateful to the #TOPMed #Omics WG for giving me an opportunity to learn and contribute to this important work 🧬
Cross-cohort analysis of expression and splicing quantitative trait loci in TOPMed
Most genetic variants associated with complex traits and diseases occur in non-coding genomic regions and are hypothesized to regulate gene expression. To understand the genetics underlying gene expre...
www.medrxiv.org
February 28, 2025 at 3:47 PM
An amazing amount of work here eQTL and sQTL with n>14k donors! Bravo.
27% of GWAS signals colocalized only with _secondary_ e/sQTL signals in the locus... important to think about this as we try to understand mechanisms
27% of GWAS signals colocalized only with _secondary_ e/sQTL signals in the locus... important to think about this as we try to understand mechanisms
📣 Our 2nd Blog post on improving #sQTL modeling and why it matters #RNASplicing #Genetics #Statistics #QTL biociphers.wordpress.com/2025/01/28/a...
A Deep Dive into sQTL Modeling – Part 2
In my previous post, I described how, in our recent sQTL preprint, we broke current sQTL pipelines into their basic elements. This led to identifying potential issues/areas we may be able to improv…
biociphers.wordpress.com
January 29, 2025 at 4:05 AM
📣 Our 2nd Blog post on improving #sQTL modeling and why it matters #RNASplicing #Genetics #Statistics #QTL biociphers.wordpress.com/2025/01/28/a...
If you like larger sample sizes, then do check out our reprocessed and fine mapped cis-eQTLs and cis-sQTLs (leafCutter and MAJIQ!) from the INTERVAL cohort (whole blood, n up to 4,729)!
zenodo.org/records/1795...
These will be on the eQTL Catalogue FTP soon as well.
cc @yosephbarash.bsky.social
zenodo.org/records/1795...
These will be on the eQTL Catalogue FTP soon as well.
cc @yosephbarash.bsky.social
Fine mapped eQTL and sQTL summary statistics from the INTERVAL RNA-seq study (part 1)
This repository contains fine mapped eQTL and sQTL summary statistics from the INTERVAL RNA-seq study (Tokolyi et al, 2025). Datasets QTD001000-QTD001002 are based on the whole cohort of 4,729 samples...
zenodo.org
January 7, 2026 at 10:24 AM
If you like larger sample sizes, then do check out our reprocessed and fine mapped cis-eQTLs and cis-sQTLs (leafCutter and MAJIQ!) from the INTERVAL cohort (whole blood, n up to 4,729)!
zenodo.org/records/1795...
These will be on the eQTL Catalogue FTP soon as well.
cc @yosephbarash.bsky.social
zenodo.org/records/1795...
These will be on the eQTL Catalogue FTP soon as well.
cc @yosephbarash.bsky.social
📢 Thrilled to see this out, an atlas of e/sQTL across multiple tissues and diverse ancestries in 14,324 TOPMed participants: www.medrxiv.org/content/10.1...
Grateful to the #TOPMed #Omics WG for giving me an opportunity to learn and contribute to this important work 🧬
Grateful to the #TOPMed #Omics WG for giving me an opportunity to learn and contribute to this important work 🧬
Cross-cohort analysis of expression and splicing quantitative trait loci in TOPMed
Most genetic variants associated with complex traits and diseases occur in non-coding genomic regions and are hypothesized to regulate gene expression. To understand the genetics underlying gene expre...
www.medrxiv.org
February 25, 2025 at 8:48 PM
📢 Thrilled to see this out, an atlas of e/sQTL across multiple tissues and diverse ancestries in 14,324 TOPMed participants: www.medrxiv.org/content/10.1...
Grateful to the #TOPMed #Omics WG for giving me an opportunity to learn and contribute to this important work 🧬
Grateful to the #TOPMed #Omics WG for giving me an opportunity to learn and contribute to this important work 🧬
For those who don't know it, I really think the fivex #eqtl/ #sqtl browser is one of the most useful and intuitive tools when doing detective work on a new #gwas hit.
fivex.sph.umich.edu
Much thanks to all its creators & @kauralasoo.bsky.social & team for the upstream work on the eqtl catalogue.
fivex.sph.umich.edu
Much thanks to all its creators & @kauralasoo.bsky.social & team for the upstream work on the eqtl catalogue.
FIVEx: eQTL Browser
fivex.sph.umich.edu
March 28, 2025 at 1:38 PM
For those who don't know it, I really think the fivex #eqtl/ #sqtl browser is one of the most useful and intuitive tools when doing detective work on a new #gwas hit.
fivex.sph.umich.edu
Much thanks to all its creators & @kauralasoo.bsky.social & team for the upstream work on the eqtl catalogue.
fivex.sph.umich.edu
Much thanks to all its creators & @kauralasoo.bsky.social & team for the upstream work on the eqtl catalogue.
So nice to be back home in Korea and excited to be at #OARSI2025! Stop by poster #595 where I’m presenting on chromatin accessibility QTLs in resting/FNF-stimulated primary human chondrocytes. I’ve been integrating eQTL, sQTL, and Hi-C data to better understand gene regulation in osteoarthritis.
April 25, 2025 at 2:37 PM
So nice to be back home in Korea and excited to be at #OARSI2025! Stop by poster #595 where I’m presenting on chromatin accessibility QTLs in resting/FNF-stimulated primary human chondrocytes. I’ve been integrating eQTL, sQTL, and Hi-C data to better understand gene regulation in osteoarthritis.
Key reads from last week on human genetics, multiomics, and precision medicine 🧵
1⃣New e/sQTL resource from TOPMed
In 14,324 whole blood & tissue samples the study detects cis- and trans-e/sQTLs and colocalizes them with 10,000 GWAS signals for 164 traits.
🔗 www.medrxiv.org/content/10.1...
1⃣New e/sQTL resource from TOPMed
In 14,324 whole blood & tissue samples the study detects cis- and trans-e/sQTLs and colocalizes them with 10,000 GWAS signals for 164 traits.
🔗 www.medrxiv.org/content/10.1...
February 24, 2025 at 4:09 PM
Key reads from last week on human genetics, multiomics, and precision medicine 🧵
1⃣New e/sQTL resource from TOPMed
In 14,324 whole blood & tissue samples the study detects cis- and trans-e/sQTLs and colocalizes them with 10,000 GWAS signals for 164 traits.
🔗 www.medrxiv.org/content/10.1...
1⃣New e/sQTL resource from TOPMed
In 14,324 whole blood & tissue samples the study detects cis- and trans-e/sQTLs and colocalizes them with 10,000 GWAS signals for 164 traits.
🔗 www.medrxiv.org/content/10.1...
📣 New post re our recent findings/methods dev for #sQTL #RNA #Splicing #RNA-Seq. We think this will be highly useful/impactful for (s)QTL detection/quantification. Hope to get (constructive 😉) feedback and much usage from the community! 😀 biociphers.wordpress.com/2025/01/20/a...
A Deep Dive into sQTL Modeling – Part 1
The next few blog posts will be dedicated to a high level overview of our preprint on splicing QTL (sQTL) modeling: “A Deep Dive into Statistical Modeling of RNA Splicing QTLs Reveals New Variants …
biociphers.wordpress.com
January 20, 2025 at 4:45 PM
📣 New post re our recent findings/methods dev for #sQTL #RNA #Splicing #RNA-Seq. We think this will be highly useful/impactful for (s)QTL detection/quantification. Hope to get (constructive 😉) feedback and much usage from the community! 😀 biociphers.wordpress.com/2025/01/20/a...
One of those truly multiomic studies. Get to see sQTL, eQTL, pQTL, mQTL connect genetic etiology across molecular traits and health outcomes
📣 New from the lab: The contribution of genetic determinants of blood gene expression and splicing to molecular phenotypes and health outcomes www.nature.com/articles/s41...
Check out the INTERVAL RNAseq portal www.intervalrna.org.uk
Led by @alextokolyi.bsky.social & Elodie Persyn!
Check out the INTERVAL RNAseq portal www.intervalrna.org.uk
Led by @alextokolyi.bsky.social & Elodie Persyn!
March 5, 2025 at 6:15 AM
One of those truly multiomic studies. Get to see sQTL, eQTL, pQTL, mQTL connect genetic etiology across molecular traits and health outcomes
A great resource of single-cell splicing QTLs from the Asian Immune Diversity Atlas❗️
👉474 PBMC samples
👉1M cells analyed with scRNAseq
👉11,577 independent cell-specific cis-sQTLs
📜paper: nature.com/articles/s4158…
📊sQTL summ stats: zenodo.org/records/8343365
👉474 PBMC samples
👉1M cells analyed with scRNAseq
👉11,577 independent cell-specific cis-sQTLs
📜paper: nature.com/articles/s4158…
📊sQTL summ stats: zenodo.org/records/8343365
December 5, 2024 at 4:33 PM
A great resource of single-cell splicing QTLs from the Asian Immune Diversity Atlas❗️
👉474 PBMC samples
👉1M cells analyed with scRNAseq
👉11,577 independent cell-specific cis-sQTLs
📜paper: nature.com/articles/s4158…
📊sQTL summ stats: zenodo.org/records/8343365
👉474 PBMC samples
👉1M cells analyed with scRNAseq
👉11,577 independent cell-specific cis-sQTLs
📜paper: nature.com/articles/s4158…
📊sQTL summ stats: zenodo.org/records/8343365
And the same variant is also a fine mapped sQTL (PIP ~ 0.99 in multiple studies) in the @eqtlcatalogue.bsky.social
elixir.ut.ee/eqtl/?rsid=r...
elixir.ut.ee/eqtl/?rsid=r...
March 4, 2025 at 7:55 PM
And the same variant is also a fine mapped sQTL (PIP ~ 0.99 in multiple studies) in the @eqtlcatalogue.bsky.social
elixir.ut.ee/eqtl/?rsid=r...
elixir.ut.ee/eqtl/?rsid=r...
What happens when AI meets human genetics?
We integrate single-cell sQTL mapping with fine-mapping and deep-learning splicing prediction to uncover disease causal genetic variants and their mechanisms. Read our new study in Genome Biology: link.springer.com/article/10.1...
We integrate single-cell sQTL mapping with fine-mapping and deep-learning splicing prediction to uncover disease causal genetic variants and their mechanisms. Read our new study in Genome Biology: link.springer.com/article/10.1...
Integrating single-cell sQTL mapping with deep-learning splicing prediction identifies causal variants under influenza infection - Genome Biology
Background Realizing the full potential of human genetics requires identifying causal variants and genes underlying association signals. Molecular quantitative trait locus (molQTL) analyses, such as e...
link.springer.com
August 31, 2026 at 7:53 PM
What happens when AI meets human genetics?
We integrate single-cell sQTL mapping with fine-mapping and deep-learning splicing prediction to uncover disease causal genetic variants and their mechanisms. Read our new study in Genome Biology: link.springer.com/article/10.1...
We integrate single-cell sQTL mapping with fine-mapping and deep-learning splicing prediction to uncover disease causal genetic variants and their mechanisms. Read our new study in Genome Biology: link.springer.com/article/10.1...
Also, at OAS1/OAS2/OASL lupus locus, I think it is quite likely that eQTL variants might act via multiple genes. We do see a sQTL colocalisation specifically with OAS1, but this does not preclude other paralogs(?) from having a causal effect.
June 9, 2025 at 8:10 PM
Also, at OAS1/OAS2/OASL lupus locus, I think it is quite likely that eQTL variants might act via multiple genes. We do see a sQTL colocalisation specifically with OAS1, but this does not preclude other paralogs(?) from having a causal effect.
In INTERVAL dataset we've actually run fine mapping both with imputed genotypes (n = 4,729) and WGS genotypes (n = 2,892). Superficially the WGS analysis gave much smallel credible sets (desipte the smaller sample size) but truly benchmarking fine mapping is quite tricky. zenodo.org/records/1795...
Fine mapped eQTL and sQTL summary statistics from the INTERVAL RNA-seq study (part 1)
This repository contains fine mapped eQTL and sQTL summary statistics from the INTERVAL RNA-seq study (Tokolyi et al, 2025). Datasets QTD001000-QTD001002 are based on the whole cohort of 4,729 samples...
zenodo.org
January 7, 2026 at 11:59 AM
In INTERVAL dataset we've actually run fine mapping both with imputed genotypes (n = 4,729) and WGS genotypes (n = 2,892). Superficially the WGS analysis gave much smallel credible sets (desipte the smaller sample size) but truly benchmarking fine mapping is quite tricky. zenodo.org/records/1795...
I have been calling caQTLs and combining eQTL and sQTL data from the same cell types as those in our previously published papers, and also using Hi-C to explore long-range caQTLs and eQTLs, as well as new Osteoarthritis GWAS data from this year.
October 15, 2025 at 5:28 AM
I have been calling caQTLs and combining eQTL and sQTL data from the same cell types as those in our previously published papers, and also using Hi-C to explore long-range caQTLs and eQTLs, as well as new Osteoarthritis GWAS data from this year.
Authors published a paper in Biorxiv, they used SQTL in the study. Including #RRIDs will make this less ambiguous.
SciScore made a table with this resource, see “Automated Services” module (download as csv, xml or #jats) #RRID #reproducibility
SciScore made a table with this resource, see “Automated Services” module (download as csv, xml or #jats) #RRID #reproducibility
Sex-specific Genetic Regulatory Effects in Chickens
www.biorxiv.org
March 4, 2026 at 1:00 PM
Authors published a paper in Biorxiv, they used SQTL in the study. Including #RRIDs will make this less ambiguous.
SciScore made a table with this resource, see “Automated Services” module (download as csv, xml or #jats) #RRID #reproducibility
SciScore made a table with this resource, see “Automated Services” module (download as csv, xml or #jats) #RRID #reproducibility
Sharing our exciting single-cell splicing method ISSAC. Key features include:
1) ISSAC is 1.4 to 2.5-fold power increase over LeafCutter on single-cell sQTL discovery, and scalable to millions of cells
2) ISSAC is able to map cell-state-dependent sQTLs and intron-retention sQTLs.
1) ISSAC is 1.4 to 2.5-fold power increase over LeafCutter on single-cell sQTL discovery, and scalable to millions of cells
2) ISSAC is able to map cell-state-dependent sQTLs and intron-retention sQTLs.
May 9, 2026 at 2:29 PM
Sharing our exciting single-cell splicing method ISSAC. Key features include:
1) ISSAC is 1.4 to 2.5-fold power increase over LeafCutter on single-cell sQTL discovery, and scalable to millions of cells
2) ISSAC is able to map cell-state-dependent sQTLs and intron-retention sQTLs.
1) ISSAC is 1.4 to 2.5-fold power increase over LeafCutter on single-cell sQTL discovery, and scalable to millions of cells
2) ISSAC is able to map cell-state-dependent sQTLs and intron-retention sQTLs.
I've been wondering for a while if someone (maybe you) has a sense of the proportion of missense variants that are also e/sQTL on a different gene than the one they act on as missense. We find one here (and it indeed acted as a red herring!)
Genome-wide analyses of neonatal jaundice reveal a marked departure from adult bilirubin metabolism - Nature Communications
The underlying causes of neonatal jaundice are not well understood. Here, the authors identify genetic variants associated with neonatal jaundice, including a variant in the gene UGT1A, finding a dist...
www.nature.com
March 4, 2025 at 8:24 PM
I've been wondering for a while if someone (maybe you) has a sense of the proportion of missense variants that are also e/sQTL on a different gene than the one they act on as missense. We find one here (and it indeed acted as a red herring!)
METHODS: We curated 181 EDCs and identified 1,116 EDC-related genes through chemical-gene interaction network analysis, followed by integration of multi-omics quantitative trait loci datasets (eQTL, sQTL, mQTL, and pQTL) to derive genetic instruments. (🧵 4/14)
June 9, 2026 at 10:51 AM
METHODS: We curated 181 EDCs and identified 1,116 EDC-related genes through chemical-gene interaction network analysis, followed by integration of multi-omics quantitative trait loci datasets (eQTL, sQTL, mQTL, and pQTL) to derive genetic instruments. (🧵 4/14)
Causal splicing variants revealed by deep-learning integration of single-cell sQTL mapping under influenza infection #SingleCell 🧪🧬🖥️
https://www.researchsquare.com/article/rs-8408992/latest
https://www.researchsquare.com/article/rs-8408992/latest
January 9, 2026 at 8:01 AM
Causal splicing variants revealed by deep-learning integration of single-cell sQTL mapping under influenza infection #SingleCell 🧪🧬🖥️
https://www.researchsquare.com/article/rs-8408992/latest
https://www.researchsquare.com/article/rs-8408992/latest
3) Applied to 3 million DLPFC single-nuc data, we identified more than 33,000 cell-type-specific sQTLs, as well as cell-state-dependent and G x disease sQTLs.
4) We validated the genetic mechanism of TRPT1 sQTL which also underlies neuroticism risk
4) We validated the genetic mechanism of TRPT1 sQTL which also underlies neuroticism risk
May 9, 2026 at 2:29 PM
3) Applied to 3 million DLPFC single-nuc data, we identified more than 33,000 cell-type-specific sQTLs, as well as cell-state-dependent and G x disease sQTLs.
4) We validated the genetic mechanism of TRPT1 sQTL which also underlies neuroticism risk
4) We validated the genetic mechanism of TRPT1 sQTL which also underlies neuroticism risk
We identified a pathway from genetic variants -> cis-eQTL (of a splicing factor) -> trans-sQTL (of a key T-cell differentiation marker) -> T-cell proportions (of naive vs. memory T cells). All of these are inferred using a single population-scale single-cell dataset.
December 5, 2024 at 3:28 AM
We identified a pathway from genetic variants -> cis-eQTL (of a splicing factor) -> trans-sQTL (of a key T-cell differentiation marker) -> T-cell proportions (of naive vs. memory T cells). All of these are inferred using a single population-scale single-cell dataset.
Dynamic AS and dynamic sQTLs are widespread along the B-cell development trajectory, some of which may be implicated in disease. For example, PAX5 dynamic isoforms are key determinants of B cell differentiation, and CLEC2D dynamic sQTL is colocalized with autoimmune disease.
December 5, 2024 at 3:28 AM
Dynamic AS and dynamic sQTLs are widespread along the B-cell development trajectory, some of which may be implicated in disease. For example, PAX5 dynamic isoforms are key determinants of B cell differentiation, and CLEC2D dynamic sQTL is colocalized with autoimmune disease.