PT - JOURNAL ARTICLE AU - Zheng, An AU - Lamkin, Michael AU - Qiu, Yutong AU - Ren, Kevin AU - Goren, Alon AU - Gymrek, Melissa TI - A flexible simulation toolkit for designing and evaluating ChIP-sequencing experiments AID - 10.1101/624486 DP - 2019 Jan 01 TA - bioRxiv PG - 624486 4099 - http://biorxiv.org/content/early/2019/05/01/624486.short 4100 - http://biorxiv.org/content/early/2019/05/01/624486.full AB - A major challenge in evaluating quantitative ChIP-seq analyses, such as peak calling and differential binding, is a lack of reliable ground truth data. We present Tulip, a toolkit for rapidly simulating ChIP-seq data using statistical models of the experimental steps. Tulip may be used for a range of applications, including power analysis for experimental design, benchmarking of analysis tools, and modeling effects of processes such as replication on ChIP-seq signals.