<HashMap><database>GEO</database><file_versions><headers><Content-Type>application/xml</Content-Type></headers><body><files><Other>ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE300nnn/GSE300647/</Other></files><type>primary</type></body><statusCode>OK</statusCode><statusCodeValue>200</statusCodeValue></file_versions><scores/><additional><omics_type>Genomics</omics_type><species> Mus musculus</species><species>Homo sapiens</species><gds_type>Genome binding/occupancy profiling by high throughput sequencing</gds_type><full_dataset_link>https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE300647</full_dataset_link><repository>GEO</repository><entry_type>GSE</entry_type></additional><is_claimable>false</is_claimable><name>Ryder: Epigenome Normalization and Variable Feature Identification</name><description>Sequencing-based epigenomic profiling significantly advances our understanding of chromatin regulation, yet inherent technical variability complicates accurate cross-sample comparisons. We introduce Ryder, a flexible Python package leveraging stable internal reference regions to perform robust genome-wide normalization. Ryder effectively reduces technical artifacts, distinguishes biological signals, and identifies variable genomic regions across diverse assays, including DNase-seq, ATAC-seq, MNase-seq, and ChIP-seq, with or without spike-in controls.</description><dates><publication>2026/04/14</publication></dates><accession>GSE300647</accession><cross_references><GSM>GSM9065803</GSM><GSM>GSM9065801</GSM><GSM>GSM9065802</GSM><GSM>GSM9065799</GSM><GSM>GSM9065800</GSM><GSM>GSM9065797</GSM><GSM>GSM9065798</GSM><GSM>GSM9065796</GSM><GPL>24247</GPL><GPL>25526</GPL><GSE>300647</GSE><taxon> Mus musculus</taxon><taxon>Homo sapiens</taxon><PMID>[41889905]</PMID></cross_references></HashMap>