# Tools for Metabolomics Data

## Documentation for package ‘metabolomicsR’ version 1.0.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

assayData | get assayData
assayData-method | get assayData
assayData<- | set assayData
assayData<--method | set assayData
batch_norm | batch normalization
bridge | bridge different data sets based on conversion factors
column_missing_rate | column missing rate
column_missing_rate.default | column missing rate
column_missing_rate.Metabolite | column missing rate
correlation | correlation of features between two Metabolite objects
create_Metabolite | Create a Metabolite object
df_plasma | Example data.
featureData | get featureData
featureData-method | get featureData
featureData<- | set featureData
featureData<--method | set featureData
filter_column_constant | filter columns if values are constant
filter_column_constant.default | filter columns if values are constant
filter_column_constant.Metabolite | filter columns if values are constant
filter_column_missing_rate | filter columns using missing rate
filter_column_missing_rate.default | filter columns using missing rate
filter_column_missing_rate.Metabolite | filter columns using missing rate
filter_row_missing_rate | filter rows using missing rate
filter_row_missing_rate.default | filter rows using missing rate
filter_row_missing_rate.Metabolite | filter rows using missing rate
fit_cox | available regression methods
fit_glmer | available regression methods
fit_lm | available regression methods
fit_lme | available regression methods
fit_lmer | available regression methods
fit_logistic | available regression methods
fit_poisson | available regression methods
impute | impute missing values
impute.default | impute missing values
impute.Metabolite | impute missing values
impute_kNN | impute missing values
inverse_rank_transform | rank-based inverse normal transformation
is_outlier | is outlier
load_data | Load metabolite data from three separate files
load_excel | Load metabolite data from an excel file
merge_data | merge two Metabolite objects
Metabolite | The Metabolite class
Metabolite-class | The Metabolite class
modelling_norm | LOESS normalization
nearestQC_norm | nearest QC sample normalization
outlier_rate | outlier rate
outlier_rate.data.frame | outlier rate
outlier_rate.default | outlier rate
outlier_rate.Metabolite | outlier rate
pareto_scale | pareto scale transformation
plot_injection_order | injection order scatterplot
plot_Metabolite | plot a Metabolite object
plot_PCA | plot PCA
plot_ROC | ROC
plot_tsne | plot tSNE
plot_UMAP | Plot UMAP
plot_volcano | volcano plot for regression results
QCmatrix_norm | QCmatrix normalization
QC_pipeline | quality control pipeline
regression | regression analysis
regression_each | regression analysis
replace_outlier | change outlier values as NA or winsorize
replace_outlier.data.frame | change outlier values as NA or winsorize
replace_outlier.default | change outlier values as NA or winsorize
replace_outlier.Metabolite | change outlier values as NA or winsorize
row_missing_rate | row missing rate
row_missing_rate.default | row missing rate
row_missing_rate.Metabolite | row missing rate
RSD | RSD
run_PCA | Principal Components Analysis
sampleData | get sampleData
sampleData-method | get sampleData
sampleData<- | set sampleData
sampleData<--method | set sampleData
save_data | Save metabolite data
show-method | Print a Metabolite class object
subset | subset a Metabolite object.
subset.Metabolite | subset a Metabolite object.
transformation | apply transformation to a Metabolite object
update_Metabolite | Update a Metabolite object