F-Seq: A Feature Density Estimator for High-Throughput Sequence Tags

Tag sequencing using high-throughput sequencing technologies are now regularly employed to identify specific sequence features such as transcription factor binding sites (ChIP-seq) or regions of open chromatin (DNase-seq). To intuitively summarize and display individual sequence data as an accurate and interpretable signal, we developed F-Seq, a software package that generates a continuous tag sequence density estimation allowing identification of biologically meaningful sites whose output can be displayed directly in the UCSC Genome Browser.

GSAA: Gene Set Association Analysis

GSAA is a computational method that integrates gene expression analysis with genome wide association studies (GWAS) to determine whether a priori defined sets of genes shows statistically significant, concordant differences with respect to gene expression profiles and genotypes between two biological states. Gene sets are generally a group of genes, such as genes in a biological pathway, that are putatively functionally related, co-regulated, or tightly linked on the same chromosome.