MOTIVATION: Accurate motif enrichment analyses depend on the choice of background DNA sequences used, which should ideally match the sequence composition of the foreground sequences. It is important to avoid false positive enrichment due to sequence biases in the genome, such as GC-bias. Therefore, relying on an appropriate set of background sequences is crucial for enrichment analysis. RESULTS: We developed BiasAway, a command line tool and its dedicated easy-to-use web server to generate synthetic sequences matching any k-mer nucleotide composition or select genomic DNA sequences matching the mononucleotide composition of the foreground sequences through four different models. For genomic sequences, we provide precomputed partitions of genomes from nine species with five different bin sizes to generate appropriate genomic background sequences. AVAILABILITY AND IMPLEMENTATION: BiasAway source code is freely available from Bitbucket (https://bitbucket.org/CBGR/biasaway) and can be easily installed using bioconda or pip. The web server is available at https://biasaway.uio.no and a detailed documentation is available at https://biasaway.readthedocs.io. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Summary: JASPAR is a widely used open-access database of curated, non-redundant transcription factor binding profiles. Currently, data from JASPAR can be retrieved as flat files or by using programming language-specific interfaces. Here, we present a programming language-independent application programming interface (API) to access JASPAR data using the Representational State Transfer (REST) architecture. The REST API enables programmatic access to JASPAR by most programming languages and returns data in eight widely used formats. Several endpoints are available to access the data and an endpoint is available to infer the TF binding profile(s) likely bound by a given DNA binding domain protein sequence. Additionally, it provides an interactive browsable interface for bioinformatics tool developers. Availability and implementation: This REST API is implemented in Python using the Django REST Framework. It is accessible at http://jaspar.genereg.net/api/ and the source code is freely available at https://bitbucket.org/CBGR/jaspar under GPL v3 license. Contact: [email protected] or [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.

BACKGROUND: A common task for scientists relies on comparing lists of genes or genomic regions derived from high-throughput sequencing experiments. While several tools exist to intersect and visualize sets of genes, similar tools dedicated to the visualization of genomic region sets are currently limited. RESULTS: To address this gap, we have developed the Intervene tool, which provides an easy and automated interface for the effective intersection and visualization of genomic region or list sets, thus facilitating their analysis and interpretation. Intervene contains three modules: venn to generate Venn diagrams of up to six sets, upset to generate UpSet plots of multiple sets, and pairwise to compute and visualize intersections of multiple sets as clustered heat maps. Intervene, and its interactive web ShinyApp companion, generate publication-quality figures for the interpretation of genomic region and list sets. CONCLUSIONS: Intervene and its web application companion provide an easy command line and an interactive web interface to compute intersections of multiple genomic and list sets. They have the capacity to plot intersections using easy-to-interpret visual approaches. Intervene is developed and designed to meet the needs of both computer scientists and biologists. The source code is freely available at https://bitbucket.org/CBGR/intervene , with the web application available at https://asntech.shinyapps.io/intervene .