Tools for Metabolomics Data


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Documentation for package ‘metabolomicsR’ version 1.0.0

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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