jChIP: a graphical environment for exploratory ChIP-Seq data analysis

BackgroundChromatin immunoprecipitation coupled with next-generation sequencing (ChIP-Seq) provides a powerful tool for discovering protein-DNA interactions. Still, the computational analysis of the great amount of ChIP-Seq data generated, involving mapping of raw data to reference genome, has been a bottle neck for most of researchers in the transcriptional and epigenetic fields. Thus, user-friendly ChIP-Seq processing method sare much needed to enable greater community of computational and bench biologists to exploit the power of ChIP-Seq technology .FindingsjChIP is a graphical tool that was developed to analyze and display ChIP-Seq data. It matches reads to the corresponding loci downloaded from Ensembl Genes or Ensembl Regulation databases. jChIP provides a friendly interface for exploratory analysis of mapped reads as well as peak calling data. The built-in functions for graphical display of reads distribution allows to evaluate the quality and meaning of ChIP-Seq data.ConclusionjChIP is a user-friendly GUI-based software for the analysis of ChIP-Seq data within context of known genomic features. Further, jChIP provides tools for discovering new and refining known genome-wide protein binding patterns.

[1]  Marc D. Perry,et al.  ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia , 2012, Genome research.

[2]  David Haussler,et al.  The UCSC Genome Browser database: 2014 update , 2013, Nucleic Acids Res..

[3]  Olivier Elemento,et al.  An integrated ChIP-seq analysis platform with customizable workflows , 2011, BMC Bioinformatics.

[4]  Terrence S. Furey,et al.  The UCSC Genome Browser Database , 2003, Nucleic Acids Res..

[5]  Jun Song,et al.  CEAS: cis-regulatory element annotation system , 2006, Nucleic Acids Res..

[6]  T. Furey.  ChIP – seq and beyond : new and improved methodologies to detect and characterize protein – DNA interactions , 2012 .

[7]  William Stafford Noble,et al.  Sequence features and chromatin structure around the genomic regions bound by 119 human transcription factors , 2012, Genome research.

[8]  Damian Smedley,et al.  BioMart – biological queries made easy , 2009, BMC Genomics.

[9]  Wing Hung Wong,et al.  Using CisGenome to Analyze ChIP‐chip and ChIP‐seq Data , 2011, Current protocols in bioinformatics.

[10]  Tao Ye,et al.  seqMINER: an integrated ChIP-seq data interpretation platform , 2010, Nucleic acids research.

[11]  Aaron R. Quinlan,et al.  Bioinformatics Applications Note Genome Analysis Bedtools: a Flexible Suite of Utilities for Comparing Genomic Features , 2022 .

[12]  P. Park.  ChIP–seq: advantages and challenges of a maturing technology , 2009, Nature Reviews Genetics.

[13]  C. Glass,et al.  Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. , 2010, Molecular cell.