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Chromatin immunoprecipitation with high-throughput sequencing (ChIP-seq) provides insights into both the genomic location occupied by the protein of interest and the difference in DNA occupancy between experimental states. Given that ChIP-seq data are collected experimentally, an important step for determining regions with differential DNA occupancy between states is between-sample normalization. While between-sample normalization is crucial for downstream differential binding analysis, the technical conditions underlying between-sample normalization methods have yet to be examined for ChIP-seq. We identify three important technical conditions underlying ChIP-seq between-sample normalization methods: balanced differential DNA occupancy, equal total DNA occupancy, and equal background binding across states. To illustrate the importance of satisfying the selected normalization method's technical conditions for downstream differential binding analysis, we simulate ChIP-seq read count data where different combinations of the technical conditions are violated. We then externally verify our simulation results using experimental data. Based on our findings, we suggest that researchers use their understanding of the ChIP-seq experiment at hand to guide their choice of between-sample normalization method. Alternatively, researchers can use a high-confidence peakset, which is the intersection of the differentially bound peaksets obtained from using different between-sample normalization methods. In our two experimental analyses, roughly half of the called peaks were called as differentially bound for every normalization method. High-confidence peaks are less sensitive to one's choice of between-sample normalization method, and thus could be a more robust basis for identifying genomic regions with differential DNA occupancy between experimental states when there is uncertainty about which technical conditions are satisfied.
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http://dx.doi.org/10.1093/bib/bbaf431 | DOI Listing |
Brief Bioinform
July 2025
Department of Mathematics & Statistics, Pomona College, 610 N. College Ave, Claremont, CA 91711, United States.
Chromatin immunoprecipitation with high-throughput sequencing (ChIP-seq) provides insights into both the genomic location occupied by the protein of interest and the difference in DNA occupancy between experimental states. Given that ChIP-seq data are collected experimentally, an important step for determining regions with differential DNA occupancy between states is between-sample normalization. While between-sample normalization is crucial for downstream differential binding analysis, the technical conditions underlying between-sample normalization methods have yet to be examined for ChIP-seq.
View Article and Find Full Text PDFPharm Stat
August 2025
Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Sample size determination in Bayesian randomized phase II trial design often relies on computationally intensive search methods, presenting challenges in terms of feasibility and efficiency. We propose a novel approach that greatly reduces the computing time of sample size calculations for Bayesian trial designs. Our approach innovatively connects group sequential design with Bayesian trial design and leverages the proportional relationship between sample size and the squared drift parameter.
View Article and Find Full Text PDFBioinform Adv
June 2025
Data Science Institute, Hasselt University, Hasselt 3500, Belgium.
High-throughput techniques for biological and (bio)medical sciences often result in read counts used in downstream analysis. Nowadays, complex experimental designs in combination with these high-throughput methods are regularly applied and lead to correlated count-data measured from matched samples or taken from the same subject under multiple treatment conditions. Additionally, as is common with biological data, the variance is often larger than the mean, leading to over dispersed count data.
View Article and Find Full Text PDFDiagnostics (Basel)
May 2025
Central Institute for Clinical Chemistry and Laboratory Diagnostics, Medical Faculty, Heinrich Heine University, University Hospital, Moorenstraße 5, 40225 Düsseldorf, Germany.
: Clinical experience indicates that the determination of interleukin 6 (IL-6) in human blood can vary depending on time span between sample collection and centrifugation. Here, we evaluated confounding effects in various blood specimens. : The blood of healthy individuals and critically ill patients was collected in EDTA-, heparin-, and serum collection tubes.
View Article and Find Full Text PDFIntroduction: Characterisation of carotid artery stenosis by Doppler ultrasound relies on peak systolic velocity (PSV) measurements and velocity ratios. The site of PSV sampling is conventionally guided by 2-dimensional (2D) colour Doppler in the longitudinal plane only. The recently introduced Philips eXL14-3 MHz matrix array transducer (Philips Ultrasound, Bothell, WA, USA) allows visualisation of colour Doppler in longitudinal and transverse planes simultaneously (3D).
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