Mingyang Cai1, Fan Gao2, Wange Lu3, Kai Wang4. 1. Department of Preventive Medicine Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research Zilkha Neurogenetic Institute. 2. Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research Zilkha Neurogenetic Institute. 3. Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research Department of Stem Cell Biology and Regenerative Medicine. 4. Zilkha Neurogenetic Institute Department of Psychiatry, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA.
Abstract
Circularized Chromosome Conformation Capture followed by deep sequencing (4C-Seq) is a powerful technique to identify genome-wide partners interacting with a pre-specified genomic locus. Here, we present a computational and statistical approach to analyze 4C-Seq data generated from both enzyme digestion and sonication fragmentation-based methods. We implemented a command line software tool and a web interface called w4CSeq, which takes in the raw 4C sequencing data (FASTQ files) as input, performs automated statistical analysis and presents results in a user-friendly manner. Besides providing users with the list of candidate interacting sites/regions, w4CSeq generates figures showing genome-wide distribution of interacting regions, and sketches the enrichment of key features such as TSSs, TTSs, CpG sites and DNA replication timing around 4C sites. AVAILABILITY AND IMPLEMENTATION: Users can establish their own web server by downloading source codes at https://github.com/WGLab/w4CSeq Additionally, a demo web server is available at http://w4cseq.wglab.org CONTACT: kaiwang@usc.edu or wangelu@usc.eduSupplementary information: Supplementary data are available at Bioinformatics online.
Circularized Chromosome Conformation Capture followed by deep sequencing (4C-Seq) is a powerful technique to identify genome-wide partners interacting with a pre-specified genomic locus. Here, we present a computational and statistical approach to analyze 4C-Seq data generated from both enzyme digestion and sonication fragmentation-based methods. We implemented a command line software tool and a web interface called w4CSeq, which takes in the raw 4C sequencing data (FASTQ files) as input, performs automated statistical analysis and presents results in a user-friendly manner. Besides providing users with the list of candidate interacting sites/regions, w4CSeq generates figures showing genome-wide distribution of interacting regions, and sketches the enrichment of key features such as TSSs, TTSs, CpG sites and DNA replication timing around 4C sites. AVAILABILITY AND IMPLEMENTATION: Users can establish their own web server by downloading source codes at https://github.com/WGLab/w4CSeq Additionally, a demo web server is available at http://w4cseq.wglab.org CONTACT: kaiwang@usc.edu or wangelu@usc.eduSupplementary information: Supplementary data are available at Bioinformatics online.
Authors: Harmen J G van de Werken; Paula J P de Vree; Erik Splinter; Sjoerd J B Holwerda; Petra Klous; Elzo de Wit; Wouter de Laat Journal: Methods Enzymol Date: 2012 Impact factor: 1.600
Authors: Henrik Devitt Møller; Marghoob Mohiyuddin; Iñigo Prada-Luengo; M Reza Sailani; Jens Frey Halling; Peter Plomgaard; Lasse Maretty; Anders Johannes Hansen; Michael P Snyder; Henriette Pilegaard; Hugo Y K Lam; Birgitte Regenberg Journal: Nat Commun Date: 2018-03-14 Impact factor: 14.919