# Metabolomics and Spectral Data Analysis and Mining

## 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