#statisticalgenetics — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #statisticalgenetics, aggregated by home.social.
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A highly sensitive analytical blood-testing method that uses classical statistics to isolate and analyze samples containing as little as 5% cancer DNA.
#Oncology #StatisticalGenetics #MathematicalBiology #MolecularPathology #sflorg
https://www.sflorg.com/2026/06/ongy06092601.html -
A highly sensitive analytical blood-testing method that uses classical statistics to isolate and analyze samples containing as little as 5% cancer DNA.
#Oncology #StatisticalGenetics #MathematicalBiology #MolecularPathology #sflorg
https://www.sflorg.com/2026/06/ongy06092601.html -
A highly sensitive analytical blood-testing method that uses classical statistics to isolate and analyze samples containing as little as 5% cancer DNA.
#Oncology #StatisticalGenetics #MathematicalBiology #MolecularPathology #sflorg
https://www.sflorg.com/2026/06/ongy06092601.html -
Mike Boehnke is retiring and here is information on his symposium: Boehnke Symposium Building Modern Statistical Genetics and Shaping its Future May 14–15, 2026 | Michigan League | Ann Arbor, MI #StatGen #StatisticalGenetics #Genetics sites.google.com/umich.edu/bo...
Boehnke Symposium -
The Dept. of Human Genetics at the Univ. of Pittsburgh School of Public Health seeks applicants for a tenure-stream faculty position at the rank of Assistant or Associate Professor. We welcome applicants from all quantitative genetics/genomics fields to reinforce or expand the department’s strengths in statistical and computational genetics/genomics, genetic epidemiology, and bioinformatics.
#Genetics #StatisticalGenetics #Statistics #Genomics #Bioinformatics
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The Dept. of Human Genetics at the Univ. of Pittsburgh School of Public Health seeks applicants for a tenure-stream faculty position at the rank of Assistant or Associate Professor. We welcome applicants from all quantitative genetics/genomics fields to reinforce or expand the department’s strengths in statistical and computational genetics/genomics, genetic epidemiology, and bioinformatics.
#Genetics #StatisticalGenetics #Statistics #Genomics #Bioinformatics
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The Dept. of Human Genetics at the Univ. of Pittsburgh School of Public Health seeks applicants for a tenure-stream faculty position at the rank of Assistant or Associate Professor. We welcome applicants from all quantitative genetics/genomics fields to reinforce or expand the department’s strengths in statistical and computational genetics/genomics, genetic epidemiology, and bioinformatics.
#Genetics #StatisticalGenetics #Statistics #Genomics #Bioinformatics
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STATGEN 2024 talk
A Kernel-Based Neural Network for High-dimensional Risk Prediction on Massive Genetic Data
Qing LuNeural Network
Nonlinear
Non-additiveKernel-Based Neural Network (KNN)
kernel matrics constructed based on the genetic variables.Related preprint:
An Association Test Based on Kernel-Based Neural Networks for Complex Genetic Association Analysis
https://arxiv.org/abs/2312.066691/
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STATGEN 2024 talk
A Kernel-Based Neural Network for High-dimensional Risk Prediction on Massive Genetic Data
Qing LuNeural Network
Nonlinear
Non-additiveKernel-Based Neural Network (KNN)
kernel matrics constructed based on the genetic variables.Related preprint:
An Association Test Based on Kernel-Based Neural Networks for Complex Genetic Association Analysis
https://arxiv.org/abs/2312.066691/
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STATGEN 2024 talk
A Kernel-Based Neural Network for High-dimensional Risk Prediction on Massive Genetic Data
Qing LuNeural Network
Nonlinear
Non-additiveKernel-Based Neural Network (KNN)
kernel matrics constructed based on the genetic variables.Related preprint:
An Association Test Based on Kernel-Based Neural Networks for Complex Genetic Association Analysis
https://arxiv.org/abs/2312.066691/
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STATGEN 2024 talk
Improved methods for empirical Bayes multivariate multiple testing and effect size estimation
Yunqi YangEmpirical Bayes multivariate normal means (EBMNM) model [Urbut et al., 2019]
Allow for heterogeneous sharing of eQTLs in multiple tissues (e.g., some are shared across all tissues, some are shared only within brain tissues, etc.)
Truncated Eigenvalue Decomposition
udr: Ultimate Deconvolution in R
https://stephenslab.github.io/udr/ -
STATGEN 2024 talk
Improved methods for empirical Bayes multivariate multiple testing and effect size estimation
Yunqi YangEmpirical Bayes multivariate normal means (EBMNM) model [Urbut et al., 2019]
Allow for heterogeneous sharing of eQTLs in multiple tissues (e.g., some are shared across all tissues, some are shared only within brain tissues, etc.)
Truncated Eigenvalue Decomposition
udr: Ultimate Deconvolution in R
https://stephenslab.github.io/udr/ -
STATGEN 2024 talk
Improved methods for empirical Bayes multivariate multiple testing and effect size estimation
Yunqi YangEmpirical Bayes multivariate normal means (EBMNM) model [Urbut et al., 2019]
Allow for heterogeneous sharing of eQTLs in multiple tissues (e.g., some are shared across all tissues, some are shared only within brain tissues, etc.)
Truncated Eigenvalue Decomposition
udr: Ultimate Deconvolution in R
https://stephenslab.github.io/udr/ -
STATGEN 2024 talk
MultiSTAAR: A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies
Xihao LiFunctionally-informed Multi-Trait MultiSTAAR approach.
MultiSTAAR-O: Omnibus test
1. Burden
2. SKAT
3. ACAT-VLi X et al. A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies. bioRxiv doi: 10.1101/2023.10.30.564764.
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STATGEN 2024 talk
MultiSTAAR: A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies
Xihao LiFunctionally-informed Multi-Trait MultiSTAAR approach.
MultiSTAAR-O: Omnibus test
1. Burden
2. SKAT
3. ACAT-VLi X et al. A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies. bioRxiv doi: 10.1101/2023.10.30.564764.
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STATGEN 2024 talk
MultiSTAAR: A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies
Xihao LiFunctionally-informed Multi-Trait MultiSTAAR approach.
MultiSTAAR-O: Omnibus test
1. Burden
2. SKAT
3. ACAT-VLi X et al. A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies. bioRxiv doi: 10.1101/2023.10.30.564764.
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STATGEN 2024 talk
Adventures in Human Genetics: Purpose, Serendipity, Innovation
Gonçalo Abecasis"It is important to think carefully about what is the right question, and what are the right statistics. But there is a lot of opportunity in thinking about what is the best design to answer the question."
Goal
Understand disease
Treat
Predict disease
PreventCan learn from natural experiments in millions of people.
1/
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STATGEN 2024 talk
Adventures in Human Genetics: Purpose, Serendipity, Innovation
Gonçalo Abecasis"It is important to think carefully about what is the right question, and what are the right statistics. But there is a lot of opportunity in thinking about what is the best design to answer the question."
Goal
Understand disease
Treat
Predict disease
PreventCan learn from natural experiments in millions of people.
1/
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STATGEN 2024 talk
Adventures in Human Genetics: Purpose, Serendipity, Innovation
Gonçalo Abecasis"It is important to think carefully about what is the right question, and what are the right statistics. But there is a lot of opportunity in thinking about what is the best design to answer the question."
Goal
Understand disease
Treat
Predict disease
PreventCan learn from natural experiments in millions of people.
1/
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STATGEN 2024 talk
Working towards Inclusivity in Genetic Studies: Estimating accurate population structure with Small Reference Sample Sizes
Souha TifourArriaga-MacKenzie et al Summix: A method for detecting and adjusting for population structure in genetic summary data. Am J Hum Genet. 2021 Jul 1;108(7):1270-1282. doi: 10.1016/j.ajhg.2021.05.016.
Summix relies on reference populations, but what if the ref pop is small?
1/
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STATGEN 2024 talk
Working towards Inclusivity in Genetic Studies: Estimating accurate population structure with Small Reference Sample Sizes
Souha TifourArriaga-MacKenzie et al Summix: A method for detecting and adjusting for population structure in genetic summary data. Am J Hum Genet. 2021 Jul 1;108(7):1270-1282. doi: 10.1016/j.ajhg.2021.05.016.
Summix relies on reference populations, but what if the ref pop is small?
1/
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STATGEN 2024 talk
Working towards Inclusivity in Genetic Studies: Estimating accurate population structure with Small Reference Sample Sizes
Souha TifourArriaga-MacKenzie et al Summix: A method for detecting and adjusting for population structure in genetic summary data. Am J Hum Genet. 2021 Jul 1;108(7):1270-1282. doi: 10.1016/j.ajhg.2021.05.016.
Summix relies on reference populations, but what if the ref pop is small?
1/
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STATGEN 2024 talk
Genotype prediction of 336,463 samples from public expression data
Afrooz Razirecount3: uniformly processed RNA-seq
https://rna.recount.bio/We developed a statistical model to predict genotypes from the Recount3 data
It has high prediction accuracy.
1/
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STATGEN 2024 talk
Genotype prediction of 336,463 samples from public expression data
Afrooz Razirecount3: uniformly processed RNA-seq
https://rna.recount.bio/We developed a statistical model to predict genotypes from the Recount3 data
It has high prediction accuracy.
1/
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STATGEN 2024 talk
Genotype prediction of 336,463 samples from public expression data
Afrooz Razirecount3: uniformly processed RNA-seq
https://rna.recount.bio/We developed a statistical model to predict genotypes from the Recount3 data
It has high prediction accuracy.
1/
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STATGEN 2024 talk
BRCAPRO+BCRAT: extending a Mendelian breast cancer risk prediction model to include non-genetic risk factors
Zoe GuanBRCAPRO: Mendelian model, genes
BCRAT: 1st family hx, hormonal risk factors, hx of benign disease
Combine these complementary models.
https://www.mdpi.com/2072-6694/15/4/1090
#STATGEN2024 #Genetics #BreastCancer #RiskPrediction #StatisticalGenetics
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STATGEN 2024 talk
BRCAPRO+BCRAT: extending a Mendelian breast cancer risk prediction model to include non-genetic risk factors
Zoe GuanBRCAPRO: Mendelian model, genes
BCRAT: 1st family hx, hormonal risk factors, hx of benign disease
Combine these complementary models.
https://www.mdpi.com/2072-6694/15/4/1090
#STATGEN2024 #Genetics #BreastCancer #RiskPrediction #StatisticalGenetics
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STATGEN 2024 talk
BRCAPRO+BCRAT: extending a Mendelian breast cancer risk prediction model to include non-genetic risk factors
Zoe GuanBRCAPRO: Mendelian model, genes
BCRAT: 1st family hx, hormonal risk factors, hx of benign disease
Combine these complementary models.
https://www.mdpi.com/2072-6694/15/4/1090
#STATGEN2024 #Genetics #BreastCancer #RiskPrediction #StatisticalGenetics
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STATGEN 2024 talk
Polygenic risk score analysis for multiethnic populations
Chris AmosPolygenic Risk Scores (PRS)
* Inform re biological processes
* Identify some at higher risk
* Might motivate behavioral changePRS could inform when to start screening.
"measles plot instead of a manhattan plot" - has excessive false positives all over the genome.
Lung cancer risk snp also is related to response to smoking cessation
1/
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STATGEN 2024 talk
Polygenic risk score analysis for multiethnic populations
Chris AmosPolygenic Risk Scores (PRS)
* Inform re biological processes
* Identify some at higher risk
* Might motivate behavioral changePRS could inform when to start screening.
"measles plot instead of a manhattan plot" - has excessive false positives all over the genome.
Lung cancer risk snp also is related to response to smoking cessation
1/
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STATGEN 2024 talk
Polygenic risk score analysis for multiethnic populations
Chris AmosPolygenic Risk Scores (PRS)
* Inform re biological processes
* Identify some at higher risk
* Might motivate behavioral changePRS could inform when to start screening.
"measles plot instead of a manhattan plot" - has excessive false positives all over the genome.
Lung cancer risk snp also is related to response to smoking cessation
1/
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STATGEN 2024 talk
Bayesian Meta-Analysis of Penetrance for Cancer Risk with Adjustment for Ascertainment Bias
Swati BiswasNeed accurate estimates of age-specific penetrance for cancer risk variants.
https://arxiv.org/abs/2304.01912Heterogeneous studies w/ different measures of risk
Marabelli et al. Penetrance of ATM Gene Mutations in Breast Cancer: A Meta-Analysis of Different Measures of Risk. Genet Epidemiol. 2016 doi: 10.1002/gepi.219711/
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STATGEN 2024 talk
Bayesian Meta-Analysis of Penetrance for Cancer Risk with Adjustment for Ascertainment Bias
Swati BiswasNeed accurate estimates of age-specific penetrance for cancer risk variants.
https://arxiv.org/abs/2304.01912Heterogeneous studies w/ different measures of risk
Marabelli et al. Penetrance of ATM Gene Mutations in Breast Cancer: A Meta-Analysis of Different Measures of Risk. Genet Epidemiol. 2016 doi: 10.1002/gepi.219711/
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STATGEN 2024 talk
Bayesian Meta-Analysis of Penetrance for Cancer Risk with Adjustment for Ascertainment Bias
Swati BiswasNeed accurate estimates of age-specific penetrance for cancer risk variants.
https://arxiv.org/abs/2304.01912Heterogeneous studies w/ different measures of risk
Marabelli et al. Penetrance of ATM Gene Mutations in Breast Cancer: A Meta-Analysis of Different Measures of Risk. Genet Epidemiol. 2016 doi: 10.1002/gepi.219711/
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STATGEN 2024 talk
Improving Genetic Risk Prediction with Genetic Architecture and Functional Annotations
Wei JiangGenome-wide Empirical Bayes to use both genetic architecture and functional annotations in a computationally efficient way.
* Summary-statistics-based
* No parameter tuning needed
* Has improved prediction accuracy over existing methods. -
STATGEN 2024 talk
Improving Genetic Risk Prediction with Genetic Architecture and Functional Annotations
Wei JiangGenome-wide Empirical Bayes to use both genetic architecture and functional annotations in a computationally efficient way.
* Summary-statistics-based
* No parameter tuning needed
* Has improved prediction accuracy over existing methods. -
STATGEN 2024 talk
Improving Genetic Risk Prediction with Genetic Architecture and Functional Annotations
Wei JiangGenome-wide Empirical Bayes to use both genetic architecture and functional annotations in a computationally efficient way.
* Summary-statistics-based
* No parameter tuning needed
* Has improved prediction accuracy over existing methods. -
STATGEN 2024 talk
Novel Methods for Estimating Risk Parameters Associated with Polygenic Scores Using Case-Parent Trio Designs
Ziqiao WangEstimates of SNP effect sizes can be biased due to
* Population stratification
* Assortative matingPrior method
PRS TDT (pTDT) (Weiner et al., Nat Genet 2017)Goal
To develop a joint model that is flexible and robustAssume family PGS ~ multivariate normal distribution w/ family-specfic mean & var
1/
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STATGEN 2024 talk
Novel Methods for Estimating Risk Parameters Associated with Polygenic Scores Using Case-Parent Trio Designs
Ziqiao WangEstimates of SNP effect sizes can be biased due to
* Population stratification
* Assortative matingPrior method
PRS TDT (pTDT) (Weiner et al., Nat Genet 2017)Goal
To develop a joint model that is flexible and robustAssume family PGS ~ multivariate normal distribution w/ family-specfic mean & var
1/
-
STATGEN 2024 talk
Novel Methods for Estimating Risk Parameters Associated with Polygenic Scores Using Case-Parent Trio Designs
Ziqiao WangEstimates of SNP effect sizes can be biased due to
* Population stratification
* Assortative matingPrior method
PRS TDT (pTDT) (Weiner et al., Nat Genet 2017)Goal
To develop a joint model that is flexible and robustAssume family PGS ~ multivariate normal distribution w/ family-specfic mean & var
1/
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STATGEN 2024 talk
Linking variants to gene networks with multivariate association approaches
Xuanyao LiuDetecting trans-eQTLs is challenging
- Small trans- effects
- Multiple-testing correction
- Overwhelmed by false positivesTrans-PCO method
PCO = PC-based omnibus test
https://github.com/liliw-w/Trans
1/
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STATGEN 2024 talk
Linking variants to gene networks with multivariate association approaches
Xuanyao LiuDetecting trans-eQTLs is challenging
- Small trans- effects
- Multiple-testing correction
- Overwhelmed by false positivesTrans-PCO method
PCO = PC-based omnibus test
https://github.com/liliw-w/Trans
1/
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STATGEN 2024 talk
Linking variants to gene networks with multivariate association approaches
Xuanyao LiuDetecting trans-eQTLs is challenging
- Small trans- effects
- Multiple-testing correction
- Overwhelmed by false positivesTrans-PCO method
PCO = PC-based omnibus test
https://github.com/liliw-w/Trans
1/
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STATGEN 2024 talk
Localizing Rare-Variant Association Regions via Multiple Testing Embedded in an Aggregation Tree
Jichun XieWhich variants
* Gene region
* Sliding window (fixed size)
* Varying window
DYNamic Aggregation TEsting (DYNATE) algorithm"DYNATE dynamically and hierarchically aggregates smaller genomic regions into larger ones"
https://cran.r-project.org/package=DYNATE
1/
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STATGEN 2024 talk
Localizing Rare-Variant Association Regions via Multiple Testing Embedded in an Aggregation Tree
Jichun XieWhich variants
* Gene region
* Sliding window (fixed size)
* Varying window
DYNamic Aggregation TEsting (DYNATE) algorithm"DYNATE dynamically and hierarchically aggregates smaller genomic regions into larger ones"
https://cran.r-project.org/package=DYNATE
1/
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STATGEN 2024 talk
Localizing Rare-Variant Association Regions via Multiple Testing Embedded in an Aggregation Tree
Jichun XieWhich variants
* Gene region
* Sliding window (fixed size)
* Varying window
DYNamic Aggregation TEsting (DYNATE) algorithm"DYNATE dynamically and hierarchically aggregates smaller genomic regions into larger ones"
https://cran.r-project.org/package=DYNATE
1/
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STATGEN 2024 talk
Quantile regression GWAS with related samples
Fan WangQuantile regression tests whether a genetic variant associates with various quantiles of a trait.
Quantile Rank Score test
- Distribution-free
No transformation needed.
- Very fast
Estimate the null model only once.
- R package: QRank https://cran.r-project.org/package=QRank1/
#STATGEN2024 #StatisticalGenetics #Genetics #QuantileRegression
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STATGEN 2024 talk
Quantile regression GWAS with related samples
Fan WangQuantile regression tests whether a genetic variant associates with various quantiles of a trait.
Quantile Rank Score test
- Distribution-free
No transformation needed.
- Very fast
Estimate the null model only once.
- R package: QRank https://cran.r-project.org/package=QRank1/
#STATGEN2024 #StatisticalGenetics #Genetics #QuantileRegression
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STATGEN 2024 talk
Quantile regression GWAS with related samples
Fan WangQuantile regression tests whether a genetic variant associates with various quantiles of a trait.
Quantile Rank Score test
- Distribution-free
No transformation needed.
- Very fast
Estimate the null model only once.
- R package: QRank https://cran.r-project.org/package=QRank1/
#STATGEN2024 #StatisticalGenetics #Genetics #QuantileRegression
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STATGEN 2024 talk
Distinct explanations underlie gene-environment interactions in the UK Biobank.
Arun DurvasulaGenetic effects across the genome may exhibit context dependence
- European vs. East Asian genetic correlation is less than 1 across a wide range of traits.
- Hinting at polygenic GxEGxE can arise through different scenarios
- Imperfect genetic correlation
- Varying genetic variance
- Proportional amplification1/
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STATGEN 2024 talk
Distinct explanations underlie gene-environment interactions in the UK Biobank.
Arun DurvasulaGenetic effects across the genome may exhibit context dependence
- European vs. East Asian genetic correlation is less than 1 across a wide range of traits.
- Hinting at polygenic GxEGxE can arise through different scenarios
- Imperfect genetic correlation
- Varying genetic variance
- Proportional amplification1/
-
STATGEN 2024 talk
Distinct explanations underlie gene-environment interactions in the UK Biobank.
Arun DurvasulaGenetic effects across the genome may exhibit context dependence
- European vs. East Asian genetic correlation is less than 1 across a wide range of traits.
- Hinting at polygenic GxEGxE can arise through different scenarios
- Imperfect genetic correlation
- Varying genetic variance
- Proportional amplification1/
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STATGEN 2024 talk
The influence of antipsychotic exposure on genetic susceptibility to obesity
Anne JusticeMany factors contribute to obesity risk, including medications.
Obesity Related to Antipsychotic Liability & Exposure (ORAcLE) Genetics Consortium
https://sites.wustl.edu/oracle/Examine polygenic risk scores (PRS) for antipsychotic-induced weight gain in Geisinger MyCode, which began in 2007. 184,293 with genotype & whole exome data.
1/
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STATGEN 2024 talk
The influence of antipsychotic exposure on genetic susceptibility to obesity
Anne JusticeMany factors contribute to obesity risk, including medications.
Obesity Related to Antipsychotic Liability & Exposure (ORAcLE) Genetics Consortium
https://sites.wustl.edu/oracle/Examine polygenic risk scores (PRS) for antipsychotic-induced weight gain in Geisinger MyCode, which began in 2007. 184,293 with genotype & whole exome data.
1/
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STATGEN 2024 talk
The influence of antipsychotic exposure on genetic susceptibility to obesity
Anne JusticeMany factors contribute to obesity risk, including medications.
Obesity Related to Antipsychotic Liability & Exposure (ORAcLE) Genetics Consortium
https://sites.wustl.edu/oracle/Examine polygenic risk scores (PRS) for antipsychotic-induced weight gain in Geisinger MyCode, which began in 2007. 184,293 with genotype & whole exome data.
1/
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STATGEN 2024 talk
Detecting latent systemic structure in deep phenotyping and genotyping data
Audrey HendricksExpecting systemic structure S to be the same/similar across all the traits.
Trait_i = X_i + E_i + (O_i + S)
How to infer S?
Multitrait finite mixture of regressions (MFMR) by Dahl et al (2019)
1/
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STATGEN 2024 talk
Detecting latent systemic structure in deep phenotyping and genotyping data
Audrey HendricksExpecting systemic structure S to be the same/similar across all the traits.
Trait_i = X_i + E_i + (O_i + S)
How to infer S?
Multitrait finite mixture of regressions (MFMR) by Dahl et al (2019)
1/
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STATGEN 2024 talk
Detecting latent systemic structure in deep phenotyping and genotyping data
Audrey HendricksExpecting systemic structure S to be the same/similar across all the traits.
Trait_i = X_i + E_i + (O_i + S)
How to infer S?
Multitrait finite mixture of regressions (MFMR) by Dahl et al (2019)
1/
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STATGEN 2024 talk
Statistical Methods for Single-Cell RNA-Seq Analysis and Spatial Transcriptomics
Rafael IrizarrytSNE and UMAP plots:
"They really aren't informative, but they are really pretty."Negative control scRNAseq data set: the percent of zeros is very high, and contributes strongly to the first PCA. tSNE plot 'discovers' new cells.
Transformed to log2(1 + CPM): looks zero-inflated.
Raw counts: Poisson
1/
#Genetics #STATGEN2024 #StatisticalGenetics #RNAseq #Transcriptomics
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STATGEN 2024 talk
Statistical Methods for Single-Cell RNA-Seq Analysis and Spatial Transcriptomics
Rafael IrizarrytSNE and UMAP plots:
"They really aren't informative, but they are really pretty."Negative control scRNAseq data set: the percent of zeros is very high, and contributes strongly to the first PCA. tSNE plot 'discovers' new cells.
Transformed to log2(1 + CPM): looks zero-inflated.
Raw counts: Poisson
1/
#Genetics #STATGEN2024 #StatisticalGenetics #RNAseq #Transcriptomics