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However, most methods commonly used for the normalization of ChIP-seq binding intensity signals across conditions, <jats:italic>e.g.<\/jats:italic>, the normalization to the same number of reads, either assume a constant signal-to-noise ratio across conditions or base the estimates of correction factors on genomic regions with intrinsically different signals between conditions. Inaccurate normalization of ChIP-seq signal may, in turn, lead to erroneous biological conclusions.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>We developed a new R package, CHIPIN, that allows normalizing ChIP-seq signals across different conditions\/samples when spike-in information is not available, but gene expression data are at hand. Our normalization technique is based on the assumption that, on average, no differences in ChIP-seq signals should be observed in the regulatory regions of genes whose expression levels are constant across samples\/conditions. In addition to normalizing ChIP-seq signals, CHIPIN provides as output a number of graphs and calculates statistics allowing the user to assess the efficiency of the normalization and qualify the specificity of the antibody used. In addition to ChIP-seq, CHIPIN can be used without restriction on open chromatin ATAC-seq or DNase hypersensitivity data. We validated the CHIPIN method on several ChIP-seq data sets and documented its superior performance in comparison to several commonly used normalization techniques.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>The CHIPIN method provides a new way for ChIP-seq signal normalization across conditions when spike-in experiments are not available. The method is implemented in a user-friendly R package available on GitHub: <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/github.com\/BoevaLab\/CHIPIN\">https:\/\/github.com\/BoevaLab\/CHIPIN<\/jats:ext-link><\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12859-021-04320-3","type":"journal-article","created":{"date-parts":[[2021,8,17]],"date-time":"2021-08-17T12:21:23Z","timestamp":1629202883000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["CHIPIN: ChIP-seq inter-sample normalization based on signal invariance across transcriptionally constant genes"],"prefix":"10.1186","volume":"22","author":[{"given":"L\u00e9lia","family":"Polit","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gwenneg","family":"Kerdivel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sebastian","family":"Gregoricchio","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michela","family":"Esposito","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christel","family":"Guillouf","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4382-7185","authenticated-orcid":false,"given":"Valentina","family":"Boeva","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,8,17]]},"reference":[{"key":"4320_CR1","doi-asserted-by":"publisher","first-page":"693","DOI":"10.1016\/j.cell.2007.02.005","volume":"128","author":"T Kouzarides","year":"2007","unstructured":"Kouzarides T. 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