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Programmatic untargeted LC-MS feature extraction in R with the modern xcms 4.x MsExperiment/XcmsExperiment API, taking raw mzML to a feature table via CentWave peak detection, retention-time alignment, peak-density correspondence, gap-filling, CAMERA redundancy collapse, and built-in QC feature filtering. Use when converting centroided LC-MS runs into a features-by-samples matrix and deciding centWave/grouping/alignment parameters. For drift correction and QC/CV filtering execution see metabolomics/normalization-qc; for metabolite identification see metabolomics/metabolite-annotation; for the MS-DIAL GUI alternative with MS2Dec deconvolution see metabolomics/msdial-preprocessing; for downstream statistics see metabolomics/statistical-analysis.
bio-metabolomics-xcms-preprocessing is an agent skill entry in ChatHome Skills, sourced from GitHub Skill Search and scored 58/100. ## Version Compatibility Reference examples tested with: xcms 4.x+ (MsExperiment/XcmsExperiment containers), Spectra 1.12+, CAMERA 1.58+ Before using code patte. As an agent skill, it packages a reusable instruction set that AI coding agents such as Codex and Claude Code can load to perform this task without hand-written glue code. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding bio-metabolomics-xcms-preprocessing to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
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## Version Compatibility Reference examples tested with: xcms 4.x+ (MsExperiment/XcmsExperiment containers), Spectra 1.12+, CAMERA 1.58+ Before using code patterns, verify installe