Epistasis Blog

From the Computational Genetics Laboratory at the University of Pennsylvania (www.epistasis.org)

Monday, December 30, 2013

Epistasis Blog Posts from 2013

January, 2013 

Gene-gene interactions in a pathway-based analysis of genetic susceptibility to bladder cancer



Complex effects of nucleotide variants in a mammalian cis-regulatory element



Four tips for success in graduate school and beyond

Gene-based testing of interactions in association studies of quantitative traits

Alternative definitions of epistasis

Role of genetic heterogeneity and epistasis in bladder cancer susceptibility and outcome: a learning classifier system approach

Multifactor dimensionality reduction reveals a three-locus epistatic interaction associated with susceptibility to pulmonary tuberculosis

ViSEN: Methodology and software for visualization of statistical epistasis networks

Statistical epistasis networks reduce the computational complexity of searching three-locus genetic models

An information-gain approach to detecting three-way epistatic interactions in genetic association studies



Things genes can't do. Shall we have pie or stew?



Probabilistic multifactor causation - what do we mean?

Journal impact factors - updated

A robustness study of parametric and non-parametric tests in model-based multifactor dimensionality reduction for epistasis detection



JAMIA special issue on Translational Bioinformatics



A simple extension of Multifactor Dimensionality Reduction (MDR) for detecting epistasis effects on quantitative traits



The effect of genetic background on genetic interaction networks



Genotype-environment interactions reveal causal pathways that mediate genetic effects on phenotype



Best paper award at Translational Bioinformatics Conference



Big data analysis on autopilot?

Wednesday, December 11, 2013

Big Data Analysis on Autopilot?

My latest editorial with Scott Williams on whether big data analysis in genomics and other disciplines has shifted into autopilot with potentially dangerous consequences for the study of human health. This paper is open-access.

Williams SM, Moore JH. Big Data analysis on autopilot? BioData Min. 2013;6(1):22. [PubMed] [PDF]