A simple new approach to variable selection in regression, with application to genetic fine map**
We introduce a simple new approach to variable selection in linear regression, with a
particular focus on quantifying uncertainty in which variables should be selected. The …
particular focus on quantifying uncertainty in which variables should be selected. The …
Fine-map** from summary data with the “Sum of Single Effects” model
In recent work, Wang et al introduced the “Sum of Single Effects”(SuSiE) model, and showed
that it provides a simple and efficient approach to fine-map** genetic variants from …
that it provides a simple and efficient approach to fine-map** genetic variants from …
A more accurate method for colocalisation analysis allowing for multiple causal variants
C Wallace - PLoS genetics, 2021 - journals.plos.org
In genome-wide association studies (GWAS) it is now common to search for, and find,
multiple causal variants located in close proximity. It has also become standard to ask …
multiple causal variants located in close proximity. It has also become standard to ask …
Functionally informed fine-map** and polygenic localization of complex trait heritability
Fine-map** aims to identify causal variants impacting complex traits. We propose
PolyFun, a computationally scalable framework to improve fine-map** accuracy by …
PolyFun, a computationally scalable framework to improve fine-map** accuracy by …
A spectrum of explainable and interpretable machine learning approaches for genomic studies
The advancement of high‐throughput genomic assays has led to enormous growth in the
availability of large‐scale biological datasets. Over the last two decades, these increasingly …
availability of large‐scale biological datasets. Over the last two decades, these increasingly …
False discovery rate control in genome-wide association studies with population structure
We present a comprehensive statistical framework to analyze data from genome-wide
association studies of polygenic traits, producing interpretable findings while controlling the …
association studies of polygenic traits, producing interpretable findings while controlling the …
Improving fine-map** by modeling infinitesimal effects
Fine-map** aims to identify causal genetic variants for phenotypes. Bayesian fine-
map** algorithms (for example, SuSiE, FINEMAP, ABF and COJO-ABF) are widely used …
map** algorithms (for example, SuSiE, FINEMAP, ABF and COJO-ABF) are widely used …
Transcriptome data are insufficient to control false discoveries in regulatory network inference
Inference of causal transcriptional regulatory networks (TRNs) from transcriptomic data
suffers notoriously from false positives. Approaches to control the false discovery rate (FDR) …
suffers notoriously from false positives. Approaches to control the false discovery rate (FDR) …
Fast and powerful conditional randomization testing via distillation
We consider the problem of conditional independence testing: given a response and
covariates, we test the null hypothesis that. The conditional randomization test was recently …
covariates, we test the null hypothesis that. The conditional randomization test was recently …
Causal inference in genetic trio studies
We introduce a method to draw causal inferences—inferences immune to all possible
confounding—from genetic data that include parents and offspring. Causal conclusions are …
confounding—from genetic data that include parents and offspring. Causal conclusions are …