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specmine (version 3.0.2)

Metabolomics and Spectral Data Analysis and Mining

Description

Provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, feature selection and pathway analysis. Case studies can be found on the website: . This package suggests 'rcytoscapejs', a package not in mainstream repositories. If you need to install it, use: devtools::install_github('cytoscape/r-cytoscape.js@v0.0.7').

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Version

Install

install.packages('specmine')

Monthly Downloads

24

Version

3.0.2

License

GPL (>= 2)

Maintainer

Miguel Rocha

Last Published

September 18th, 2020

Functions in specmine (3.0.2)

background_correction

Background correction
apply_by_groups

Apply by groups
MAIT_identify_metabolites

MAIT metabolite identification
baseline_correction

Baseline correction
apply_by_sample

Apply function to samples
aggregate_samples

Aggregate samples
apply_by_group

Apply by group
apply_by_variable

Apply function to variables
absorbance_to_transmittance

Convert absorbance to transmittance
clustering

Perform cluster analysis
aov_all_vars

Analysis of variance
count_missing_values

Count missing values
correlations_test

Correlations test
boxplot_variables

Boxplot of variables
convert_hmdb_to_kegg

Convert HMDB codes to KEGG codes.
compare_regions_by_sample

Compare regions by sample
convert_keggpathway_2_reactiongraph

Convert KEGGPathway object to graph object.
create_dataset

Create dataset
count_missing_values_per_sample

Count missing values per sample
convert_from_hyperspec

Convert from hyperspec
convert_multiple_spcmnm_to_kegg

Convert specmine metabolite codes to KEGG codes.
boxplot_vars_factor

Boxplot of variables with metadata's variable factors
convert_chebi_to_kegg

Convert CHEBI codes to KEGG codes.
count_missing_values_per_variable

Count missing values per variable
cubic_root_transform

Cubic root transformation
check_dataset

Check dataset
cachexia

Human Cachexia data
get_data

Get data
feature_selection

Perform feature selection
data_correction

Data correction
filter_feature_selection

Perform selection by filter
get_metadata

Get metadata
correlations_dataset

Dataset correlations
convert_from_chemospec

Convert from ChemoSpec
correlation_test

Correlation test of two variables or samples
get_metadata_value

Get metadata value
create_pathway_with_reactions

Creates the pathway, with reactions included in the nodes.
get_metabolights_study_files_assay

Download data files from an assay of MetaboLights study
get_metabolights_study

Download MetaboLights study files.
get_data_as_df

Get data as data frame
first_derivative

First derivative
find_equal_samples

Find equal samples
get_type

Get type of data
dendrogram_plot_col

Plot dendrogram
get_peak_values

Get peak values
get_value_label

Get value label
get_OrganismsCodes

Get all organisms in KEGG.
get_metadata_var

Get metadata variable
get_metabolights_study_metadata_assay

Download metadata file from an assay of MetaboLights study
detect_nmr_peaks_from_dataset

Detection of the peaks in an NMR spectra dataset.
get_cpd_names

Get the names of the compounds that correspond to the kegg codes given.
get_metabolights_study_samples_files

Get list of files from an assay of the MetaboLights study and saves it in a csv file.
get_paths_with_cpds_org

Get only the paths of the organism that contain one or more of the given compounds.
impute_nas_value

Impute missing values with value replacement
convert_to_hyperspec

Convert to hyperspec
convert_to_factor

Convert metadata to factor
get_x_values_as_text

Get x-axis values as text
get_data_values

Get data values
get_MetabolitePath

Returns an object of KEGGPathway of the pathway especified in pathcode.
group_peaks

Group peaks
get_data_value

Get data value
fold_change_var

Fold change applied on two variables
get_x_label

Get x-axis label
get_x_values_as_num

Get x-axis values as numbers
kmeans_clustering

Perform k-means clustering analysis
dataset_from_peaks

Dataset from peaks
missingvalues_imputation

Missing values imputation
is_spectra

Check type of data
heatmap_correlations

Correlations heatmap
merge_data_metadata

Merge data and metadata
linreg_coef_table

Linear regression coefficient table
get_sample_names

Get sample names
hierarchical_clustering

Perform hierarchical clustering analysis
linreg_all_vars

Linear Regression
fold_change

Fold change analysis
indexes_to_xvalue_interval

Get the x-values of a vector of indexes
flat_pattern_filter

Flat pattern filter
dendrogram_plot

Plot dendrogram
get_metabPaths_org

Get the metabolic pathways present in given organism.
get_files_list_per_assay

Get list of files per assay for MetaboLights study.
impute_nas_mean

Impute missing values with mean
impute_nas_median

Impute missing values with median
kmeans_result_df

Show cluster's members
merge_datasets

Merge two datasets
low_level_fusion

Low level fusion
kmeans_plot

Plot kmeans clusters
mean_centering

Mean centering
normalize

Normalize data
pca_analysis_dataset

PCA analysis (classical)
normalize_samples

Normalize samples
pca_biplot

PCA biplot
peaks_per_sample

Peaks per sample
multifactor_aov_pvalues_table

Multifactor ANOVA p-values table
plot_ttests

Plot t-tests results
peaks_per_samples

Peaks per samples
multiplot

Multiplot
plotvar_twofactor

Plot variable distribution on two factors
msc_correction

Multiplicative scatter correction
nmr_identification

NMR metabolite identification
kruskalTest_dataset

Kruskal-Wallis tests on dataset
pathway_analysis

Creates the metabolic pathway wanted. If any of the given compounds is present in the pathway, it is coloured differently.
multifactor_aov_varexp_table

Multifactor ANOVA variability explained table
pca_pairs_plot

PCA pairs plot
pca_pairs_kmeans_plot

PCA k-means pairs plot
pca_scoresplot3D

3D PCA scores plot
offset_correction

Offset correction
pca_scoresplot2D

2D PCA scores plot
get_samples_names_dx

Get sample's names from DX files
read_data_spc

Read data from SPC files
read_metadata

Read metadata
plot_spectra

Plot spectra
read_dataset_csv

Read dataset from CSV
pca_scoresplot3D_rgl

3D PCA scores plot (interactive)
impute_nas_knn

Impute missing values with KNN
read_ms_spectra

Read MS spectra
plot_spectra_simple

Plot spectra (simple)
metabolights_studies_list

List the study IDs available in the MetaboLights database.
linreg_pvalue_table

Linear regression p-values table
impute_nas_linapprox

Impute missing values with linear approximation
get_samples_names_spc

Get sample's names from SPC files
linreg_rsquared

Linear regression r-squared
linregression_onevar

Linear regression on one variable
read_dataset_spc

Read dataset from SPC files
read_dataset_dx

Read dataset from (J)DX files
ksTest_dataset

Kolmogorov-Smirnov tests on dataset
remove_peaks_interval

Remove interval of peaks
multiClassSummary

Multi Class Summary
plot_anova

Plot ANOVA results
log_transform

Logarithmic transformation.
multifactor_aov_all_vars

Multifactor ANOVA
metadata_as_variables

Metadata as variables
pca_kmeans_plot2D

2D PCA k-means plot
remove_peaks_interval_sample_list

Remove interval of peaks (sample list)
pca_kmeans_plot3D

3D PCA k-means plot (interactive)
replace_metadata_value

Replace metadata's value
read_Bruker_files

Read Bruker processed spectra.
propolis

Brazilian Propolis from different Harvest Seasons and different Agroecological Regions (dataset)
pca_screeplot

PCA scree plot
read_csvs_folder

Read CSVs from folder
read_multiple_csvs

Read multiple CSVs
read_varian_spectra_raw

Function that reads raw spectra (intensity over time spectra) from the varian format and processes them to ppm spectra.
predict_samples

Predict samples
num_samples

Get number of samples
remove_samples_by_nas

Remove samples by NAs
savitzky_golay

Savitzky-golay transformation
set_metadata

Set new metadata
subset_x_values

Subset x-values
set_sample_names

Set samples names
spectra_options

Information on the library of NMR reference spectra in our package.
num_x_values

Get number of x values
remove_variables_by_nas

Remove variables by NAs
propolisSampleList

Brazilian Propolis from different Harvest Seasons and different Agroecological Regions (sample list)
scaling

Scale dataset
plot_kstest

Plot Kolmogorov-Smirnov tests results
plot_fold_change

Plot fold change results
plot_kruskaltest

Plot Kruskal-Wallis tests results
read_spc_nosubhdr

Import for Thermo Galactic's spc file format These functions allow to import .spc files.
scaling_samples

Scale data matrix
subset_x_values_by_interval

Subset x-values by interval
transform_data

Transform data
pca_biplot3D

3D PCA biplot (interactive)
stats_by_sample

Statistics of samples
snv_dataset

Standard Normal Variate
sum_dataset

Dataset summary
transmittance_to_absorbance

Convert transmittance to absorbance
smoothing_interpolation

Smoothing interpolation
remove_data_variables

Remove data variables
remove_metadata_variables

Remove metadata's variables
pca_importance

PCA importance
plot_peaks

Plot the peaks of a MS or NMR dataset.
pca_plot_3d

3D pca plot
read_data_csv

Read CSV data
plot_regression_coefs_pvalues

Plot regression coefficient and p-values
set_x_label

Set x-label
set_value_label

Set value label
remove_x_values_by_interval

Remove x-values by interval
replace_data_value

Replace data value
pca_robust

PCA analysis (robust)
read_data_dx

Read data from (J)DX files
remove_data

Remove data
tTests_dataset

t-Tests on dataset
remove_samples

Remove samples
recursive_feature_elimination

Perform recursive feature elimination
train_and_predict

Train and predict
subset_metadata

Subset metadata
subset_random_samples

Subset random samples
subset_samples

Subset samples
summary_var_importance

Summary of variables importance
values_per_sample

Values per peak
remove_samples_by_na_metadata

Remove samples by NA on metadata
subset_samples_by_metadata_values

Subset samples by metadata values
set_x_values

Set new x-values
values_per_peak

Values per peak
stats_by_variable

Statistics of variables
subset_by_samples_and_xvalues

Subset by samples and x-values
shift_correction

Shift correction
variables_as_metadata

Variables as metadata
volcano_plot_fc_tt

Volcano plot
x_values_to_indexes

Get x-values indexes
xvalue_interval_to_indexes

Get indexes of an interval of x-values
train_classifier

Train classifier
train_models_performance

Train models