New preprint posted: Analytic solution and stationary phase approximation for the Bayesian lasso and elastic net. Related software here.
A warm welcome to Sean who has joined the group as a PhD student in the Precision Medicine Doctoral Training Programme. Sean will work on a project to identify and study tissue-specific gene networks affected by genetic variation for plasma cortisol and causally associated with cardiovascular disease phenotypes and type II diabetes, in collaboration with Filippo Menolascina and Brian Walker.
Lingfei’s paper “Efficient and accurate causal inference with hidden confounders from genome-transcriptome variation” has been published in PLOS Computational Biology. Congrats Lingfei!
Lingfei has posted a preprint Comparable variable selection with Lasso on arXiv. In this paper we propose statistical tests to evaluate the quality of a set of p-values and to compare p-values across different experimental batches. We then use these tests to show that a newly proposed lasso-based variable selection statistic allows for a unified FDR control across multiple variable selection tasks, unlike existing methods.
A PhD project in the MRC funded Precision Medicine Doctoral Training Programme is available. The project will study cortisol-responsive gene networks in cardiovascular disease and is a collaboration with Filippo Menolascina (Synthetic Biology) and Brian Walker (Cardiovascular Science). Project details and application guidelines are here. Application deadline 9 January 2017!
Pau will present a poster on “Host response processes and host-parasite interactions in Trypanosoma brucei infections” at the IV Bioinformatics and Genomics Symposium”.
We have posted a preprint “Efficient causal inference with hidden confounders from genome-transcriptome variation data”. In this paper we introduce a new method for causal inference between gene expression traits using the DNA variations in cis-regulatory regions as causal anchors. The method has been implemented in the Findr software, and validated using the DREAM5 Systems Genetics Challenge and GEUVADIS datasets.
Lingfei will give a talk at the RECOMB/ISCB Conference on Regulatory & Systems Genomics titled “Scalable causal gene network inference from genetics of gene expression data”.
Husain has successfully defended his PhD thesis “Cross-tissue regulatory gene networks in coronary atherosclerosis” at Karolinska Institute. Congratulations and good luck in your future career!