The increasing volume of ChIP-chip and ChIP-seq data being generated creates a challenge for standard, integrative and reproducible bioinformatics data analysis platforms. We developed a web-based application called Cistrome, based on the Galaxy open source framework. In addition to the standard Galaxy functions, Cistrome has 29 ChIP-chip- and ChIP-seq-specific tools in three major categories, from preliminary peak calling and correlation analyses to downstream genome feature association, gene expression analyses, and motif discovery. Cistrome is available at http://cistrome.org/ap/.

Chromatin immunoprecipitation, DNase I hypersensitivity and transposase-accessibility assays combined with high-throughput sequencing enable the genome-wide study of chromatin dynamics, transcription factor binding and gene regulation. Although rapidly accumulating publicly available ChIP-seq, DNase-seq and ATAC-seq data are a valuable resource for the systematic investigation of gene regulation processes, a lack of standardized curation, quality control and analysis procedures have hindered extensive reuse of these data. To overcome this challenge, we built the Cistrome database, a collection of ChIP-seq and chromatin accessibility data (DNase-seq and ATAC-seq) published before January 1, 2016, including 13 366 human and 9953 mouse samples. All the data have been carefully curated and processed with a streamlined analysis pipeline and evaluated with comprehensive quality control metrics. We have also created a user-friendly web server for data query, exploration and visualization. The resulting Cistrome DB (Cistrome Data Browser), available online at http://cistrome.org/db, is expected to become a valuable resource for transcriptional and epigenetic regulation studies.

Significance Studies focused on understanding how transcription factors control gene expression have shown that transcription-factor binding sites generally greatly exceed the number of regulated genes, making it challenging to identify functional binding sites. Using Notch pathway inhibitors, we identified a subset of Notch-binding sites in leukemia cell genomes that are dynamic, changing in occupancy relatively rapidly when Notch signaling is perturbed. Dynamic Notch sites are highly associated with genes that are directly regulated by Notch and mainly lie in large regulatory switches termed superenhancers, which control genes with key roles in development and cancer. This work links Notch signaling to superenhancers and suggests that assessment of transcription factor–genome dynamics can help to identify functionally important regulatory sites.

BackgroundRNA sequencing has become a ubiquitous technology used throughout life sciences as an effective method of measuring RNA abundance quantitatively in tissues and cells. The increase in use of RNA-seq technology has led to the continuous development of new tools for every step of analysis from alignment to downstream pathway analysis. However, effectively using these analysis tools in a scalable and reproducible way can be challenging, especially for non-experts.ResultsUsing the workflow management system Snakemake we have developed a user friendly, fast, efficient, and comprehensive pipeline for RNA-seq analysis. VIPER (Visualization Pipeline for RNA-seq analysis) is an analysis workflow that combines some of the most popular tools to take RNA-seq analysis from raw sequencing data, through alignment and quality control, into downstream differential expression and pathway analysis. VIPER has been created in a modular fashion to allow for the rapid incorporation of new tools to expand the capabilities. This capacity has already been exploited to include very recently developed tools that explore immune infiltrate and T-cell CDR (Complementarity-Determining Regions) reconstruction abilities. The pipeline has been conveniently packaged such that minimal computational skills are required to download and install the dozens of software packages that VIPER uses.ConclusionsVIPER is a comprehensive solution that performs most standard RNA-seq analyses quickly and effectively with a built-in capacity for customization and expansion.Electronic supplementary materialThe online version of this article (10.1186/s12859-018-2139-9) contains supplementary material, which is available to authorized users.