Review of causal discovery methods based on graphical models
A fundamental task in various disciplines of science, including biology, is to find underlying
causal relations and make use of them. Causal relations can be seen if interventions are …
causal relations and make use of them. Causal relations can be seen if interventions are …
Multi-omics approaches to disease
High-throughput technologies have revolutionized medical research. The advent of
genotyping arrays enabled large-scale genome-wide association studies and methods for …
genotyping arrays enabled large-scale genome-wide association studies and methods for …
Mendelian randomization: genetic anchors for causal inference in epidemiological studies
G Davey Smith, G Hemani - Human molecular genetics, 2014 - academic.oup.com
Observational epidemiological studies are prone to confounding, reverse causation and
various biases and have generated findings that have proved to be unreliable indicators of …
various biases and have generated findings that have proved to be unreliable indicators of …
[HTML][HTML] Best (but oft-forgotten) practices: the design, analysis, and interpretation of Mendelian randomization studies
abstract Mendelian randomization (MR) is an increasingly important tool for appraising
causality in observational epidemiology. The technique exploits the principle that genotypes …
causality in observational epidemiology. The technique exploits the principle that genotypes …
[HTML][HTML] Modelling strategies for assessing and increasing the effectiveness of new phenotyping techniques in plant breeding
New types of phenotyping tools generate large amounts of data on many aspects of plant
physiology and morphology with high spatial and temporal resolution. These new …
physiology and morphology with high spatial and temporal resolution. These new …
What should students in plant breeding know about the statistical aspects of genotype× environment interactions?
A good statistical analysis of genotype× environment interactions (G× E) is a key
requirement for progress in any breeding program. Data for G× E analyses traditionally …
requirement for progress in any breeding program. Data for G× E analyses traditionally …
Microbiome multi-omics network analysis: statistical considerations, limitations, and opportunities
The advent of large-scale microbiome studies affords newfound analytical opportunities to
understand how these communities of microbes operate and relate to their environment …
understand how these communities of microbes operate and relate to their environment …
Iterative Hessian sketch: Fast and accurate solution approximation for constrained least-squares
M Pilanci, MJ Wainwright - Journal of Machine Learning Research, 2016 - jmlr.org
This paper considers inference of causal structure in a class of graphical models called
conditional DAGs. These are directed acyclic graph (DAG) models with two kinds of …
conditional DAGs. These are directed acyclic graph (DAG) models with two kinds of …
Metabolomic profiling for the identification of novel biomarkers and mechanisms related to common cardiovascular diseases: form and function
SH Shah, WE Kraus, CB Newgard - Circulation, 2012 - Am Heart Assoc
Cardiovascular diseases (CVDs) are the leading cause of death worldwide, but their
molecular etiology remains poorly understood, in part because they develop slowly as a …
molecular etiology remains poorly understood, in part because they develop slowly as a …
[HTML][HTML] A sparse conditional Gaussian graphical model for analysis of genetical genomics data
Genetical genomics experiments have now been routinely conducted to measure both the
genetic markers and gene expression data on the same subjects. The gene expression …
genetic markers and gene expression data on the same subjects. The gene expression …