Aims to estimate the causal single nucleotide polymorphism (SNP) and the causal mark within a gene region that are influencing expression of a given gene. Pathfinder models the hierarchical relationships between genome, chromatin, and gene expression. It is based on a hierarchical statistical method. This method generates well-calibrated posterior probabilities and can prioritize SNPs and marks for functional validation.
Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA; Department of Medical Oncology, Dana Farber Cancer Institute, Boston, MA, USA; Division of Genetics, Brigham and Women’s Hospital, Boston, MA, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA; Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
Pathfinder funding source(s)
Supported by National Institutes of Health (NIH), grant number 1R01HG009120.