SpikChIP: a novel computational methodology to compare multiple ChIP-seq using spike-in chromatin

In order to evaluate cell- and disease-specific changes in the interacting strength of chromatin targets, ChIP-seq signal across multiple conditions must undergo robust normalization. However, this is not possible using the standard ChIP-seq scheme, which lacks a reference for the control of biological and experimental variabilities. While several studies have recently proposed different solutions to circumvent this problem, substantial analytical differences among methodologies could hamper the experimental reproducibility and quantitative accuracy. Here, we propose a computational method to accurately compare ChIP-seq experiments, with exogenous spike-in chromatin, across samples in a genome-wide manner by using a local regression strategy (spikChIP). In contrast to the previous methodologies, spikChIP reduces the influence of sequencing noise of spike-in material during ChIP-seq normalization, while minimizes the overcorrection of non-occupied genomic regions in the experimental ChIP-seq. We demonstrate the utility of spikChIP with both histone and non-histone chromatin protein, allowing us to monitor for experimental reproducibility and the accurate ChIP-seq comparison of distinct experimental schemes. spikChIP software is available on GitHub (https://github.com/eblancoga/spikChIP).Spanish of Economy, Industry and Competitiveness (MEIC) (BFU2016-75008-P, and PID2019-108322GB-100), “Fundación Vencer El Cancer” (VEC), the European Regional Development Fund (FEDER), and from AGAUR to L.D.C. The Ramon y Cajal program of the Ministerio de Ciencia, Innovación y Universidades and the European Social Fund under the reference number RYC-2018-025002-I, and the Instituto de Salud Carlos III-FEDER (PI19/01814), to S.A. We acknowledge the funding support of the Spanish Ministry of Science and Innovation to the EMBL partnership, the Centro de Excelencia Severo Ochoa and the CERCA Programme / Generalitat de Catalunya