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Use when after calling buildExperiment on metabolomics data to construct a SummarizedExperiment object, before performing batch correction, outlier detection, or other QC calculations that depend on ratio assay values.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
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| name | assay-ratio-computation-verification |
| description | Use when after calling buildExperiment on metabolomics data to construct a SummarizedExperiment object, before performing batch correction, outlier detection, or other QC calculations that depend on ratio assay values. |
| license | CC-BY-4.0 |
| metadata | {"edam_operation":"http://edamontology.org/operation_3435","edam_topics":["http://edamontology.org/topic_3172","http://edamontology.org/topic_0091"],"tools":["R","mzQuality","SummarizedExperiment"],"techniques":["LC-MS"],"license_tier":"open"} |
| derived_from | [{"doi":"10.1021/jasms.5c00073","title":"mzquality"}] |
| evidence_spans | ["library(mzQuality)","mzQuality is a user-friendly R package","mzQuality requires a specific format for the input data."] |
| claims | [] |
| provenance | {"collection":"https://w3id.org/holobiomicslab/asb-skill/collection/metabolomics/v2","assembled_by":"scripts/collect_metabolomics_collection.py","sources":[{"build":"coll_mzquality","doi":"10.1021/jasms.5c00073","title":"mzquality"}],"dedup_kept_from":"coll_mzquality"} |
| schema_version | 0.2.0 |
| attribution | {"generator":"AgenticScienceBuilder","original_doi":"10.1021/jasms.5c00073","all_source_dois":["10.1021/jasms.5c00073"],"zenodo_doi":"10.5281/zenodo.20794027","curators":[],"promoter":"Louis-Félix Nothias","sponsor":"CNRS & Université Côte d'Azur"} |
Verify that the ratio assay (compound area divided by internal standard area) is correctly computed in a SummarizedExperiment object, including validation of default behavior when no secondary assay is provided. This skill ensures the mathematical correctness of the normalized compound/internal standard ratios before downstream QC analyses.
After calling buildExperiment on metabolomics data to construct a SummarizedExperiment object, before performing batch correction, outlier detection, or other QC calculations that depend on ratio assay values. Essential when verifying the behavior of internal standard normalization, especially when testing edge cases such as missing or unspecified secondary assay columns.
Load metabolomics data using readData, which validates column integrity and format. Call buildExperiment on the resulting data frame, optionally specifying column mappings for compounds (features), samples (aliquots), primary assay (compound area), and secondary assay (internal standard area). Extract the 'ratio' assay from the returned SummarizedExperiment object. For cases where secondaryAssay is not provided, verify that the ratio assay equals the primary assay values element-wise (confirming an implicit divisor of 1). For cases where secondaryAssay is specified, verify that each ratio value equals the primary assay divided by the corresponding secondary assay value across all compound–sample pairs. Compare using exact equality or tolerance-based checks depending on numerical precision requirements.
path <- system.file("extdata", "example.tsv", package = "mzQuality"); combined <- readData(path); exp <- buildExperiment(combined); ratio_assay <- assay(exp, "ratio"); primary_assay <- assay(exp, "area"); all.equal(ratio_assay, primary_assay)
readData function to read in your data. It will check if all mandatory columns are present and if the data is in the correct format. Finally, the function"doAnalysis function will perform the following steps: 1. Calculate the ratio between the compounds and assigned internal standards,"