Package index
Metaboprep Object
The main S7 class behind the metaboprep R package along with class helper functions. A container for measurement, sample, and feature data.
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Metaboprep() - Metaboprep Object
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summary.Metaboprep - Summary Method for Metaboprep Object
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add_layer() - Add a Layer of Data (internal use)
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read_metabolon() - Read Metabolon Data
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read_nightingale() - Read Nightingale Data (format 1)
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read_olink() - Read and Process Olink NPX Data File
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read_somalogic() - Read and Process SomaLogic adat file
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available_data_formats() - List Available Data Formats
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export() - Export Data from a Metaboprep Object
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export_comets() - Export Data to `COMETS` format
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export_metaboanalyst() - Export Data to `MetaboAnalyst` format
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export_metaboprep() - Export Data to `Metaboprep` format
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summarise() - Summary Statistics
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feature_summary() - Feature Summary Statistics
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sample_summary() - Sample Summary Statistics
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pc_and_outliers() - Principal Component Analysis
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tree_and_independent_features() - Identify Independent Features in a Numeric Matrix
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quality_control() - Metabolite Quality Control
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available_report_templates() - List Available Report Templates
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generate_report() - Generate Output Report
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run_metaboprep1() - Metaboprep 1 pipeline
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shiny_app() - Metaboprep Shiny App
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batch_normalise() - Batch Normalisation
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feature_describe() - Summary Statistics for Features
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missingness() - Estimate Missingness
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outlier_detection() - Identify indexes of outliers in data
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outliers() - Identify Outliers
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total_peak_area() - Estimates total peak abundance
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continuous_power_plot() - continuous trait power analysis plot
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multivariate_anova() - multivariate analysis
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cramerV() - Cramer's V (phi)
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eval.power.binary.imbalanced() - Estimate power for a binary variable in an imbalanced design
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eval.power.cont() - estimate power for continuous variable
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find.PA.effect.sizes.2.sim() - identify effect sizes
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find.cont.effect.sizes.2.sim() - identify continuos trait effect sizes
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imbalanced_power_plot() - binary trait imbalanced design power analysis plot
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variable_by_factor() - ggplot2 violin plot
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clean_names() - Standardize Column or Feature Names