Metabolomics and Spectral Data Analysis and Mining

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Documentation for package ‘specmine’ version 3.1.8

• DESCRIPTION file
• User guides, package vignettes and other documentation
• Package NEWS

Help Pages

aggregate_samples	Aggregate samples
aov_all_vars	Analysis of variance
aov_one_var	Analysis of variance for one variable
apply_by_group	Apply by group
apply_by_groups	Apply by groups
convert_hmdb_to_kegg	Get kegg codes from hmdb codes:
convert_keggpathway_2_reactiongraph	Convert KEGGPathway object to graph object
convert_multiple_spcmnm_to_kegg	Get kegg codes from spcmnm codes:
count_missing_values	Count missing values
count_missing_values_per_sample	Count missing values per sample
count_missing_values_per_variable	Count missing values per variable
create_dataset	Create dataset
create_pathway_with_reactions	Creates the pathway, with reactions included in the nodes
dataset_from_peaks	Create a dataset from peak lists
filter_feature_selection	Feature Selection Using Univariate Filters
flat_pattern_filter	Flat pattern filter
get_cpd_names	Get compound names from KEGG codes
get_metabolights_study	Download a complete MetaboLights study
get_metabolights_study_files_assay	Download files for one MetaboLights assay
get_metabolights_study_metadata_assay	Get metadata for one MetaboLights assay
get_metabolights_study_samples_files	Get sample-file mapping for one MetaboLights assay
get_MetabolitePath	Returns an object of KEGGPathway of the pathway especified in pathcode
get_metabPaths_org	Get vector with paths numbers that occur in the given organism, named with the full path name:
get_OrganismsCodes	Get code, t number, full name and phylogeny of all organisms in KEGG:
get_paths_with_cpds_org	Get only the paths of the organism that contain given compounds:
get_x_label	Get x label
get_x_values_as_text	Get x values as text
impute_nas_knn	Impute missing values with kNN
impute_nas_mean	Impute missing values with mean
impute_nas_median	Impute missing values with median
impute_nas_value	Impute missing values with a constant
merge_data_metadata	Merge data and metadata
metabolights_studies_list	List public MetaboLights studies
missingvalues_imputation	Missing values imputation
multiClassSummary	Multi-class summary metrics
pathway_analysis	Creates the pathway wanted. If any of the given compounds is present in the pathway, it is coloured differently.
pca_biplot	PCA biplot
pca_biplot3D	PCA 3D biplot
pca_kmeans_plot2D	PCA 2D k-means plot
pca_kmeans_plot3D	PCA 3D k-means plot
pca_pairs_kmeans_plot	PCA pairs plot with k-means clusters
pca_pairs_plot	PCA pairs plot
pca_robust	Robust PCA analysis
pca_scoresplot2D	PCA 2D scores plot
pca_scoresplot3D	PCA 3D scores plot
pca_scoresplot3D_rgl	PCA 3D scores plot using rgl
pca_screeplot	PCA scree plot
peak_detection2d	Detect peaks in 2D NMR spectra
read_csvs_folder	Read all CSV peak files in a folder
read_dataset_csv	Reads a dataset from CSV files
read_dataset_dx	Read a dataset from JDX files
read_data_dx	Read JDX spectra files from a folder
read_metadata	Reads metadata from a CSV file
read_multiple_csvs	Read multiple CSV peak files
read_spc_nosubhdr	Import for Thermo Galactic's spc file format These functions allow to import .spc files. A detailed description of the .spc file format is available at
recursive_feature_elimination	Recursive Feature Elimination
remove_data	Remove data
remove_data_variables	Remove data variables
remove_metadata_variables	Remove metadata variables
remove_samples	Remove samples
remove_samples_by_nas	Remove samples by NAs
remove_samples_by_na_metadata	Remove samples by NA metadata
remove_variables_by_nas	Remove variables by NAs
remove_x_values_by_interval	Remove x values by interval
spectra_options	Spectra processing options
subset_by_samples_and_xvalues	Subset by samples and x values
subset_metadata	Subset metadata
subset_random_samples	Subset random samples
subset_samples	Subset samples
subset_samples_by_metadata_values	Subset samples by metadata values
subset_x_values	Subset x values
subset_x_values_by_interval	Subset x values by interval
summary_var_importance	Summarise variable importance tables
train_and_predict	Train a classifier and predict new samples
train_classifier	Train a classifier
train_models_performance	Train multiple models and compare their performance