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
STATGEN 2024 talk
A Kernel-Based Neural Network for High-dimensional Risk Prediction on Massive Genetic Data
Qing Lu
Neural Network
Nonlinear
Non-additive
Kernel-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/2312.06669
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STATGEN 2024 talk
Improved methods for empirical Bayes multivariate multiple testing and effect size estimation
Yunqi Yang
Empirical 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 Li
Functionally-informed Multi-Trait MultiSTAAR approach.
MultiSTAAR-O: Omnibus test
1. Burden
2. SKAT
3. ACAT-V
Li 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.
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
Prevent
Can learn from natural experiments in millions of people.
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STATGEN 2024 talk
Working towards Inclusivity in Genetic Studies: Estimating accurate population structure with Small Reference Sample Sizes
Souha Tifour
Arriaga-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
Genotype prediction of 336,463 samples from public expression data
Afrooz Razi
recount3: 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
BRCAPRO+BCRAT: extending a Mendelian breast cancer risk prediction model to include non-genetic risk factors
Zoe Guan
BRCAPRO: 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
Polygenic risk score analysis for multiethnic populations
Chris Amos
Polygenic Risk Scores (PRS)
* Inform re biological processes
* Identify some at higher risk
* Might motivate behavioral change
PRS 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
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STATGEN 2024 talk
Bayesian Meta-Analysis of Penetrance for Cancer Risk with Adjustment for Ascertainment Bias
Swati Biswas
Need accurate estimates of age-specific penetrance for cancer risk variants.
https://arxiv.org/abs/2304.01912
Heterogeneous 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.21971
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STATGEN 2024 talk
Improving Genetic Risk Prediction with Genetic Architecture and Functional Annotations
Wei Jiang
Genome-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 Wang
Estimates of SNP effect sizes can be biased due to
* Population stratification
* Assortative mating
Prior method
PRS TDT (pTDT) (Weiner et al., Nat Genet 2017)
Goal
To develop a joint model that is flexible and robust
Assume family PGS ~ multivariate normal distribution w/ family-specfic mean & var
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STATGEN 2024 talk
Linking variants to gene networks with multivariate association approaches
Xuanyao Liu
Detecting trans-eQTLs is challenging
- Small trans- effects
- Multiple-testing correction
- Overwhelmed by false positives
Trans-PCO method
PCO = PC-based omnibus test
https://github.com/liliw-w/Trans
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STATGEN 2024 talk
Localizing Rare-Variant Association Regions via Multiple Testing Embedded in an Aggregation Tree
Jichun Xie
Which 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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STATGEN 2024 talk
Quantile regression GWAS with related samples
Fan Wang
Quantile 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=QRank
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#STATGEN2024 #StatisticalGenetics #Genetics #QuantileRegression
STATGEN 2024 talk
Distinct explanations underlie gene-environment interactions in the UK Biobank.
Arun Durvasula
Genetic 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 GxE
GxE can arise through different scenarios
- Imperfect genetic correlation
- Varying genetic variance
- Proportional amplification
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STATGEN 2024 talk
The influence of antipsychotic exposure on genetic susceptibility to obesity
Anne Justice
Many 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.
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STATGEN 2024 talk
Detecting latent systemic structure in deep phenotyping and genotyping data
Audrey Hendricks
Expecting 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)
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STATGEN 2024 talk
Statistical Methods for Single-Cell RNA-Seq Analysis and Spatial Transcriptomics
Rafael Irizarry
tSNE 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
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#Genetics #STATGEN2024 #StatisticalGenetics #RNAseq #Transcriptomics
STATGEN 2024 talk
Identifying GxE through Mendelian Randomization
Xiaofeng Zhu
Statistical power is low and detecting GxE is a challenge.
See:
Aschard H. A perspective on interaction effects in genetic association studies. Genet Epidemiol. 2016 Dec;40(8):678-688. doi: 10.1002/gepi.21989. Epub 2016 Jul 7. PMID: 27390122; PMCID: PMC5132101.
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#Genetics #STATGEN2024 #StatisticalGenetics #MendelianRandomization
