#statgen2024 — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #statgen2024, aggregated by home.social.
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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/
-
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
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
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/
-
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/
-
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?
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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.
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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
-
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
-
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/
-
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/
-
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
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
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/
-
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
Genetic Associations with Dynamic Placental Proteins Identify Biomarkers for Hypertension in Pregnancy
Qi YanGWAS of nine placental proteins from first- and second-trimester serum. Found associations with ADAM-12, VEGF, and sFlt-1.
Mendelian Randomization gives evidence for causal relationships between placental proteins, particularly ADAM-12 and PE and gestational hypertension.
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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
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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/
-
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
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