Package index
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Metabolite-class
Metabolite
- The Metabolite class
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Metabolite2maplet()
- Convert a Metabolite object to maplet data
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QC_pipeline()
- quality control pipeline
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QC_pipeline_df()
- quality control pipeline for a simplified data.frame.
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QCmatrix_norm()
- QCmatrix normalization
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RSD()
- RSD
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anno_hmdb()
- Query metabolite ID in HMDB database
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assayData()
- get assayData
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`assayData<-`()
- set assayData
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batch_norm()
- batch normalization
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batch_norm_df()
- batch normalization for a data.frame
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bridge()
- bridge different data sets based on conversion factors
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column_missing_rate()
- column missing rate
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correlation()
- correlation of features between two Metabolite objects
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create_Metabolite()
- Create a Metabolite object
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df_plasma
- Example data.
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featureData()
- get featureData
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`featureData<-`()
- set featureData
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filter_column_constant()
calculate_column_constant()
- filter columns if values are constant
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filter_column_missing_rate()
- filter columns using missing rate
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filter_row_missing_rate()
- filter rows using missing rate
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fit_lm()
fit_logistic()
fit_poisson()
fit_cox()
fit_lme()
fit_glmer()
fit_lmer()
- available regression methods
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genuMet_makefeature()
- distinguish genuine untargeted metabolic features without QC samples
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impute()
impute_kNN()
- impute missing values
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inverse_rank_transform()
- rank-based inverse normal transformation
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is_outlier()
- is outlier
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load_data()
- Load metabolite data from three separate files
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load_excel()
- Load metabolite data from an excel file
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maplet2Metabolite()
- Convert maplet data to a Metabolite object
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merge_data()
- merge two Metabolite objects
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modelling_norm()
- LOESS normalization
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nearestQC_norm()
- nearest QC sample normalization
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outlier_rate()
- outlier rate
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pareto_scale()
- pareto scale transformation
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plot_Metabolite()
- plot a Metabolite object
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plot_PCA()
- plot PCA
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plot_QC()
- quality control visualization
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plot_ROC()
- ROC
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plot_UMAP()
- Plot UMAP
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plot_injection_order()
- injection order scatterplot
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plot_tsne()
- plot tSNE
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plot_volcano()
- volcano plot for regression results
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regression()
regression_each()
regression_each_as_outcome()
- regression analysis
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replace_outlier()
- change outlier values as NA or winsorize
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row_missing_rate()
- row missing rate
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run_PCA()
- Principal Components Analysis
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sampleData()
- get sampleData
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`sampleData<-`()
- set sampleData
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save_data_txt()
- Save metabolite data in txt files
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save_data_xls()
- Save metabolite data in an Excel file
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show(<Metabolite>)
- Print a Metabolite class object
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subset()
- subset a Metabolite object.
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transformation()
- apply transformation to a Metabolite object
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update_Metabolite()
- Update a Metabolite object