Nominating Quality Control Outliers in Genomic Profiling Studies R package OmicsQC version 1.1.1 CRAN Task View: AnomalyDetection (https://CRAN.R-project.org/view=AnomalyDetection) A method that analyzes quality control metrics from multi-sample genomic sequencing studies and nominates poor quality samples for exclusion. Per sample quality control data are transformed into z-scores and aggregated. The distribution of aggregated z-scores are modelled using parametric distributions. The parameters of the optimal model, selected either by goodness-of-fit statistics or user-designation, are used for outlier nomination. Two implementations of the Cosine Similarity Outlier Detection algorithm are provided with flexible parameters for dataset customization. Software Depends: R (>= 2.10) Imports: stats, utils, fitdistrplus, lsa, BoutrosLab.plotting.general Suggests: knitr, rmarkdown, kableExtra, dplyr, testthat (>= 3.0.0) Paul C. Boutros <PBoutros@sbpdiscovery.org> Comprehensive R Archive Network (CRAN) Anders Hugo Frelin [aut], Helen Zhu [aut], Paul C. Boutros [aut, cre] (ORCID: <https://orcid.org/0000-0003-0553-7520>) GPL-2 2026-01-24 application/tgz https://CRAN.R-project.org/package=OmicsQC doi:10.32614/CRAN.package.OmicsQC