GEOapplication/xmlftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE337nnn/GSE337966/primaryOK200GenomicsHomo sapiensGenome binding/occupancy profiling by high throughput sequencinghttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE337966GEOGSEfalseBenchmarking CUT&RUN analysis procedure using motif enrichmentWe designed a benchmarking method to evaluate peak calling procedures for CUT&RUN data and the effects of varying preprocessing approaches, such as fragment length filtering and spike-in calibration. To support this work, we generated new CUT&RUN datasets with distinct experimental characteristics alongside publicly available datasets. In particular, we produced libraries with an average read length of approximately 133 bp—longer than typical CUT&RUN read lengths—which provide higher sequencing coverage and improved read mappability. These datasets provide complementary data for evaluating how experimental characteristics influence preprocessing strategies and peak-calling performance in CUT&RUN.2026/07/18GSE337966GSM9863665GSM9863666GSM9863667GSM9863663GSM986366418573337966Homo sapiens