@inbook{86805e4e305b42d4b734243cc4af9334,
title = "User-Friendly and Interactive Analysis of ChIP-Seq Data Using EaSeq",
abstract = "ChIP-seq is a central method to gain understanding of the regulatory networks in the genome of stem cells and during differentiation. Exploration and analysis of such genome-wide data often leads to unexpected discoveries and new hypotheses. It therefore accelerates and improves the discovery phase, when scientists with biological understanding are enabled to analyze and visualize data. EaSeq ( http://easeq.net ) offers integrated exploration of genome-wide data in a visual, versatile, user-friendly, and interactive manner that connects abstract interpretations to the signal distribution at the underlying loci. Here we introduce the interface, data types, and acquisition, and guide the reader through two example workflows. These workflows will enable the reader to perform genome-wide analysis and visualization of transcription factor binding sites and histone marks. This includes making basic plots; finding, annotating, sorting, and filtering of peaks; using EaSeq as a genome browser; measuring ChIP-seq signal and calculating ratios; as well as data import and export.",
author = "Mads Lerdrup and Klaus Hansen",
year = "2020",
doi = "10.1007/978-1-0716-0301-7_2",
language = "English",
isbn = "978-1-0716-0300-0",
volume = "2117",
series = "Methods in molecular biology (Clifton, N.J.)",
publisher = "Springer",
pages = "35--63",
editor = "Kidder, {Benjamin L.}",
booktitle = "Stem Cell Transcriptional Networks",
address = "Switzerland",
}