Package ASICS. January 23, 2018
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1 Type Package Package ASICS January 23, 2018 Title Automatic Statistical Identification in Complex Spectra Version With a set of pure metabolite spectra, ASICS quantifies metabolites concentration in a complex spectrum. The identification of metabolites is performed by fitting a mixture model to the spectra of the library with a sparse penalty. The method and its statistical properties are described in Tardivel et al. (2017) <doi: /s >. Depends R (>= 2.14) Imports doparallel, ggplot2, foreach, methods, parallel, plyr, quadprog, zoo License GPL (>= 2) Encoding UTF-8 LazyData true RoxygenNote Suggests knitr, rmarkdown VignetteBuilder knitr NeedsCompilation no Author Gaëlle Lefort [aut, cre], Rémi Sevien [aut], Patrick Tardivel [aut], Nathalie Villa-Vialaneix [aut] Maintainer Gaëlle Lefort <gaelle.lefort@inra.fr> Repository CRAN Date/Publication :57:21 UTC R topics documented: ASICS ASICSUsersGuide
2 2 ASICS ASICS_multiFiles extract_concentrations pure_library resasics-class resasics-getters resasics-methods Index 10 ASICS Automatic Statistical Identification in Complex Spectra Quantification of 1D 1H NMR spectrum with ASICS method using a library of 175 pure metabolite spectra. The method is presented in Tardivel et al. (2017). ASICS(path, exclusion.areas = matrix(c(4.5, 5.1), ncol = 2), max.shift = 0.02, which.spectra = "last", library.metabolites = NULL, threshold.noise = 0.02, seed = 1234, nb.iter.signif = 400) Arguments path folder path of the Bruker files exclusion.areas definition domain of spectra to exclude (ppm) max.shift maximum chemical shift allowed (in ppm) which.spectra if more than one spectra by sample, spectra used to perform the quantification (either "first", "last" or its number). Default to "last" library.metabolites path of the library containing the references (pure metabolite spectra). If NULL, the library included in the package is used threshold.noise threshold for signal noise seed random seed to control randomness in the algorithm (used in the estimation of significativity of a given metabolite concentration) nb.iter.signif number of iterations for the estimation of significativity of a given metabolite concentration. Default to 400 An object of type resasics-class
3 ASICSUsersGuide 3 References Tardivel P., Canlet C., Lefort G., Tremblay-Franco M., Debrauwer L., Concordet D., Servien R. (2017). ASICS: an automatic method for identification and quantification of metabolites in complex 1D 1H NMR spectra. Metabolomics, 13(10): See Also resasics-class ASICS_multiFiles pure_library ## Not run: cur_path <- system.file("extdata", "example_spectra", "AG_faq_Beck01", package = "ASICS") to_exclude <- matrix(c(4.5,5.1,5.5,6.5), ncol = 2, byrow = TRUE) result <- ASICS(path = cur_path, exclusion.areas = to_exclude) ## End(Not run) ASICSUsersGuide View ASICS User s Guide Open the ASICS User s Guide (with default browser) ASICSUsersGuide() Details The function vignette("asics") will find the short ASICS vignette that describes the main functions and how to obtain the ASICS User s Guide. The User s Guide is not itself a true vignette because it is not automatically generated during the package build process. If the operating system is not Windows, then the HTML viewer used is the one given by Sys.getenv("R_BROWSER"). The HTML viewer can be changed using Sys.setenv(R_BROWSER = ). Open the ASICS User s Guide ## Not run: ASICSUsersGuide()
4 4 ASICS_multiFiles ASICS_multiFiles Automatic Statistical Identification in Complex Spectra for many files Compute ASICS on multiple spectra of a folder. ASICS_multiFiles(name.dir, ncores = 1,...) Arguments name.dir ncores folder path of the Bruker files number of cores to use. Default to 1 (no parallel processing)... further arguments to be passed to the function ASICS for specifying the parameters of the algorithm A list containing ASICS results for each spectrum. See Also ASICS, resasics-class pure_library ## Not run: cur_path <- system.file("extdata", "example_spectra", package = "ASICS") to_exclude <- matrix(c(4.5,5.1,5.5,6.5), ncol = 2, byrow = TRUE) res_multi <- ASICS_multiFiles(name.dir = cur_path, exclusion.areas = to_exclude) ## End(Not run)
5 extract_concentrations 5 extract_concentrations Extract concentrations Combine results of the multiple file ASICS function to obtain quantified relative concentrations of metabolites for each spectrum in one dataset extract_concentrations(res_asics) Arguments res_asics result of the ASICS_multiFiles function A data frame containing relative concentrations of identified metabolites for each spectrum ## Not run: cur_path <- system.file("extdata", "example_spectra", package = "ASICS") to_exclude <- matrix(c(4.5,5.1,5.5,6.5), ncol = 2, byrow = TRUE) res_multi <- ASICS_multiFiles(name.dir = cur_path, exclusion.areas = to_exclude, ncores = 2) # extract relative concentrations quantification <- extract_concentrations(res_multi) ## End(Not run) pure_library Pure spectra library The 1D 1H NMR spectra of 175 reference compounds were collected to build the spectral library. These compounds have been prepared and recorded using a Bruker Avance III HD spectrometer in the MetaToul - AXIOM Site at Toulouse (France).
6 6 resasics-class Format A list of 4 elements: name names of the metabolites grid common grid for all spectra spectra a data frame with each pure metabolite spectrum in column nb_protons number of protons of each metabolite References Tardivel P., Canlet C., Lefort G., Tremblay-Franco M., Debrauwer L., Concordet D., Servien R. (2017). ASICS: an automatic method for identification and quantification of metabolites in complex 1D 1H NMR spectra. Metabolomics, 13(10): resasics-class An S4 class to represent results of ASICS. An S4 class to represent results of ASICS. Slots original_mixture original spectrum reconstituted_mixture reconstituted spectrum with estimated concentrations ppm_grid grid (definition domain) of the spectrum (in ppm) present_metabolites a data frame with identified metabolites and their relative concentrations Note Slots can be accessed by accessor functions with the same name (see resasics-getters). See Also ASICS resasics-methods
7 resasics-getters 7 resasics-getters S4 methods to represent results of ASICS. S4 methods to represent results of ASICS. present_metabolites(object) original_mixture(object) reconstituted_mixture(object) ppm_grid(object) Arguments object an object of class resasics The respective slot from resasics object. ## Not run: cur_path <- system.file("extdata", "example_spectra", "AG_faq_Beck01", package = "ASICS") to_exclude <- matrix(c(4.5,5.1,5.5,6.5), ncol = 2, byrow = TRUE) result <- ASICS(path = cur_path, exclusion.areas = to_exclude) #Identified metabolites present_metabolites(result) ## End(Not run)
8 8 resasics-methods resasics-methods S4 methods to represent results of ASICS. S4 methods to represent results of ASICS. summary(object,...) show(object) print(x) plot(x, y, xmin = 0.5, xmax = 10, ymin = 0, ymax = NULL, add_metab = NULL) Arguments object... not used x y an object of class resasics an object of class resasics not used xmin, xmax, ymin, ymax lower and upper bounds for x and y, respectively add_metab name of one metabolite to add to the plot. Default to NULL (no pure spectrum added to the plot) plot the true and recomposed (as estimated by ASICS) spectra on one figure. In addition, one pure metabolite spectrum (as provided in the reference library) can be superimposed to the plot. See Also ASICS resasics-class
9 resasics-methods 9 ## Not run: cur_path <- system.file("extdata", "example_spectra", "AG_faq_Beck01", package = "ASICS") to_exclude <- matrix(c(4.5,5.1,5.5,6.5), ncol = 2, byrow = TRUE) result <- ASICS(path = cur_path, exclusion.areas = to_exclude) result summary(result) plot(result) ## End(Not run)
10 Index ASICS, 2, 4, 6, 8 ASICS_multiFiles, 3, 4, 5 ASICSUsersGuide, 3 extract_concentrations, 5 original_mixture (resasics-getters), 7 original_mixture,resasics-method (resasics-getters), 7 plot,resasics-method (resasics-methods), 8 plot.resasics (resasics-methods), 8 ppm_grid (resasics-getters), 7 ppm_grid,resasics-method (resasics-getters), 7 present_metabolites (resasics-getters), 7 present_metabolites,resasics-method (resasics-getters), 7 print,resasics-method (resasics-methods), 8 print.resasics (resasics-methods), 8 pure_library, 3, 4, 5 reconstituted_mixture (resasics-getters), 7 reconstituted_mixture,resasics-method (resasics-getters), 7 resasics-class, 6 resasics-getters, 6, 7 resasics-methods, 8 show,resasics-method (resasics-methods), 8 show.resasics (resasics-methods), 8 summary,resasics-method (resasics-methods), 8 summary.resasics (resasics-methods), 8 10
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Type Package Title 'Webdriver'/'Selenium' Binary Manager Version 0.2.2 Package wdman January 23, 2017 There are a number of binary files associated with the 'Webdriver'/'Selenium' project (see ,
Package fitbitscraper
Title Scrapes Data from Fitbit Version 0.1.8 Package fitbitscraper April 14, 2017 Author Cory Nissen [aut, cre] Maintainer Cory Nissen Scrapes data from Fitbit
Package cosinor. February 19, 2015
Type Package Package cosinor February 19, 2015 Title Tools for estimating and predicting the cosinor model Version 1.1 Author Michael Sachs Maintainer Michael Sachs
Package vip. June 15, 2018
Type Package Title Variable Importance Plots Version 0.1.0 Package vip June 15, 2018 A general framework for constructing variable importance plots from various types machine learning models in R. Aside
Package RMCriteria. April 13, 2018
Type Package Title Multicriteria Package Version 0.1.0 Author Pedro Albuquerque and Gustavo Monteiro Package RMCriteria April 13, 2018 BugReports https://github.com/lamfo-unb/rmcriteria Maintainer Pedro
Package tidytransit. March 4, 2019
Type Package Package tidytransit March 4, 2019 Title Read, Validate, Analyze, and Map Files in the General Transit Feed Specification Version 0.3.8 Read General Transit Feed Specification (GTFS) zipfiles
Package meme. November 2, 2017
Title Create Meme Version 0.0.7 Package meme November 2, 2017 The word 'Meme' was originated from the book, 'The Selfish Gene', authored by Richard Dawkins (1976). It is a unit of culture that is passed
Package modules. July 22, 2017
Title Self Contained Units of Source Code Version 0.6.0 Date 2017-07-18 Package modules July 22, 2017 Description Provides modules as an organizational unit for source code. Modules enforce to be more