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Background/Objectives: We present a software package called reflimR (Version 1.0.6), which enables rapid and transparent verification of reference intervals from routine laboratory measurements. Our method makes it easy to compare the results with specified target values and facilitates the interpretation of deviations using traffic light colors. Methods: The algorithm includes three procedural steps: (a) definition of an appropriate distribution model, based on Bowley's quartile skewness, (b) iterative truncation, based on a modified boxplot method to obtain the central 95% of presumably inconspicuous results, and (c) extrapolation of reference limits from a truncated normal quantile–quantile plot. Results: All algorithms have been combined into one consolidated library, which can be called in the R environment with a single command reflim (x). Using an example dataset included in the package, we demonstrate that our method can be applied to mixed data containing a substantial proportion of pathological values. It leads to similar results as the direct guideline approach as well as the more sophisticated indirect refineR software package. As compared to the latter, reflimR works much faster and needs smaller datasets for robust estimates. For the interpretation of the results, we present an intuitive color scheme based on tolerance ranges (permissible uncertainty of laboratory results). We show that a relatively high number of published reference limits require careful reevaluation. Conclusions: The reflimR package closes the gap between direct guideline methods and the more sophisticated indirect refineR method. We recommend reflimR for the rapid routine verification of large amounts of reference limits and refineR for a careful analysis of unclear or doubtful results from this check. [ABSTRACT FROM AUTHOR]

Liquid biopsies are revolutionizing the detection and management of malignant diseases. While repetitive DNA sequences, such as LINE-1 and ALU are established in cell-free DNA (cfDNA) research, their clinical applications remain limited. In this study, we explore human satellite 2 (HSATII), a prevalent repeat DNA sequence in plasma that exhibits increased levels in cancer patients, thereby positioning it as a potential pan-cancer biomarker. We employed targeted sequencing and copy number variation (CNV) analysis using two primer pairs to assess the differential abundance of HSATII sequences in the plasma of breast cancer patients compared to healthy individuals. PCR amplicons of HSATII from 10 patients and 10 control subjects were sequenced, generating 151 bp paired-end reads. By constructing a pooled reference dataset, HSATII copy ratios were estimated in the patients. Our analysis revealed several significant CNVs in HSATII, with certain sequences displaying notable gains and losses across all breast cancer patients, suggesting their potential as biomarkers. However, we observed pronounced fragmentation of cfDNA in cancer, leading to the loss of longer PCR amplicons (>180 bp). While not all observed losses can be attributed to fragmentation artifacts, this phenomenon does introduce complexity in interpreting CNV data. Notably, this research marks the first instance of targeted HSATII sequencing in a liquid biopsy context. Our findings lay the groundwork for developing sequencing-based assays to detect differentially represented HSATII sequences, potentially advancing the field of minimally-invasive cancer screening. [ABSTRACT FROM AUTHOR]