Cistrome: an integrative platform for transcriptional regulation studies

By Tao Liu, Jorge Ortiz, Len Taing, Clifford A. Meyer, Bernett Lee, Yong Zhang, Hyunjin Shin, S. Wong, Jian Ma, Y. Lei and 7 more. Genome Biology, 2011

683 citations recorded by the source corpus.

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/.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/61d824396949aee6d87935df174fdf59ddc7b78c

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Citations in the corpus

Target analysis by integration of transcriptome and ChIP-seq data with BETA (2013, methodology): “Requiring summit enrichment improves the specificity of reported motifs, and this approach has been adopted in the SeqPos algorithm in the Cistrome analysis pipeline 33 .”
dbSUPER: a database of super-enhancers in mouse and human genome (2015, methodology): “Currently, dbSUPER supports any public/personal instance of Galaxy (48) including Cistrome (50), and GREAT (49) to which data can be send directly.”
ngs.plot: Quick mining and visualization of next-generation sequencing data by integrating genomic databases (2014, methodology): “Several programs [18-20] with graphical interfaces have been developed, featuring a point-and-click workflow to perform these tasks.”
Analysing and interpreting DNA methylation data (2012, methodology): “For example, using a collection of genomic region sets obtained from Cistrome 118 and other public data sources, it has recently been shown that DMRs associated with in vivo differentiation of adult stem cells are much more strongly enriched for cell‑ type‑specific transcription factor binding than ”
Impacts of the ubiquitous factor Zelda on Bicoid-dependent DNA binding and transcription in Drosophila (2014, methodology): “Peaks were called using the MACS program with the respective genomic inputs as controls on the Cistrome platform (Zhang et al. 2008; Liu et al. 2011).”
Cistrome Data Browser: a data portal for ChIP-Seq and chromatin accessibility data in human and mouse (2016, methodology): “Finally, we performed annotation analysis, including average conservation profiles across peak regions, motif analysis (21) and putative gene target identification (22).”
Reuse of public genome-wide gene expression data (2012, methodology): “…query experiments that provide interaction information include Cistrome, which is based on chromatin immunoprecipitation followed by microarray (ChIP–chip) data and ChIP followed by high-throughput sequencing (ChIP–seq) data 27 and miRGator for microRNA expression and its regulation of mRNA 28 .”
Single-Cell DNA Methylome Sequencing and Bioinformatic Inference of Epigenomic Cell-State Dynamics (2015, methodology): “We collected 2,768 experimentally deﬁned region sets from ENCODE and other sources (ENCODE Project Consortium, 2012; Liu et al., 2011; Shefﬁeld et al., 2013), comprising cell-type-speciﬁc DNase-hy-persensitive sites, regions marked by various histone modi-ﬁcations, transcription factor binding…”
Cistrome Data Browser: expanded datasets and new tools for gene regulatory analysis (2018, background): “Cistromes, defined as genome-wide maps of the cisregulatory binding sites of trans-acting factors, are invaluable for understanding the complex biology of gene regulation (2,3).”
ChIPBase: a database for decoding the transcriptional regulation of long non-coding RNA and microRNA genes from ChIP-Seq data (2012, methodology): “Known transcription factor binding matrices were downloaded from the JASPAR (18), Transfac (19), Cistrome (20) and UniPROBE (21) databases.”