Welcome to Cistrome

The cistrome refers to "the set of cis-acting targets of a trans-acting factor on a genome-wide scale, also known as the in vivo genome-wide location of transcription factor binding-sites or histone modifications". Here we build integrative analysis pipelines (Cistrome) to help experimental biologists, and conduct efficient data integration to better mine the hidden biological insights from publicly available high throughput data.

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Cistrome Data Browser v3.0

Cistrome Data Browser 3.0 is an updated database of publicly available ChIP-seq, ATAC-seq and DNase-seq datasets. It provides maps of the genome-wide locations of transcription factors, cofactors, chromatin remodelers, histone post-translational modifications and regions of chromatin accessible to endonuclease activity.

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Cistrome Data Browser v2.0

A portal to browse public ChIP-seq and DNase-seq datasets. Besides providing a comprehensive knowledgebase of all of the publicly available ChIP-Seq and DNase-Seq data in mouse and human, it also provides functions to analysis and visualize these datasets.

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Cistrome Analysis Pipeline

An integrative and reproducible bioinformatics data analysis platform based on Galaxy open source framework. Besides 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.

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Cistrome Cancer

A comprehensive resource for predicted transcription factor (TF) targets and enhancer profiles in cancers. The prediction was from integrative analysis of TCGA expression profiles and public ChIP-seq profiles.

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A webserver for functional enrichment analysis of transcription factor binding sites.

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CistromeDB Toolkit

A webserver to help you find what factors regulate your gene of interest, what factors bind in your interval or have a significant binding overlap with your peak set by integrating datasets in CistromeDB.

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A bioinformatics tool developed to predict the transcriptional regulators (TRs) of differentially expressed or co-expressed gene sets.

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