AlpsNMR - Automated spectraL Processing System for NMR
Reads Bruker NMR data directories both zipped and unzipped. It provides automated and efficient signal processing for untargeted NMR metabolomics. It is able to interpolate the samples, detect outliers, exclude regions, normalize, detect peaks, align the spectra, integrate peaks, manage metadata and visualize the spectra. After spectra proccessing, it can apply multivariate analysis on extracted data. Efficient plotting with 1-D data is also available. Basic reading of 1D ACD/Labs exported JDX samples is also available.
Last updated 16 days ago
bioconductor-package
13 stars 2.27 score 119 dependenciesAlpsNMR - Automated spectraL Processing System for NMR
Reads Bruker NMR data directories both zipped and unzipped. It provides automated and efficient signal processing for untargeted NMR metabolomics. It is able to interpolate the samples, detect outliers, exclude regions, normalize, detect peaks, align the spectra, integrate peaks, manage metadata and visualize the spectra. After spectra proccessing, it can apply multivariate analysis on extracted data. Efficient plotting with 1-D data is also available. Basic reading of 1D ACD/Labs exported JDX samples is also available.
Last updated 22 days ago
bioconductor-package
1.24 score 119 dependenciesMassSpecWavelet - Peak Detection for Mass Spectrometry data using wavelet-based algorithms
Peak Detection in Mass Spectrometry data is one of the important preprocessing steps. The performance of peak detection affects subsequent processes, including protein identification, profile alignment and biomarker identification. Using Continuous Wavelet Transform (CWT), this package provides a reliable algorithm for peak detection that does not require any type of smoothing or previous baseline correction method, providing more consistent results for different spectra. See <doi:10.1093/bioinformatics/btl355} for further details.
Last updated 2 months ago
bioconductor-package
3.47 score 0 dependencies 21 dependentshttpuv - HTTP and WebSocket Server Library
Provides low-level socket and protocol support for handling HTTP and WebSocket requests directly from within R. It is primarily intended as a building block for other packages, rather than making it particularly easy to create complete web applications using httpuv alone. httpuv is built on top of the libuv and http-parser C libraries, both of which were developed by Joyent, Inc. (See LICENSE file for libuv and http-parser license information.)
Last updated 8 months ago
14.29 score 7 dependencies 2003 dependentscondformat - Conditional Formatting in Data Frames
Apply and visualize conditional formatting to data frames in R. It renders a data frame with cells formatted according to criteria defined by rules, using a tidy evaluation syntax. The table is printed either opening a web browser or within the 'RStudio' viewer if available. The conditional formatting rules allow to highlight cells matching a condition or add a gradient background to a given column. This package supports both 'HTML' and 'LaTeX' outputs in 'knitr' reports, and exporting to an 'xlsx' file.
Last updated 9 months ago
formattinghtmllatextablevisualisation
25 stars 2.50 score 56 dependencies 1 dependentsMassSpecWavelet - Peak Detection for Mass Spectrometry data using wavelet-based algorithms
Peak Detection in Mass Spectrometry data is one of the important preprocessing steps. The performance of peak detection affects subsequent processes, including protein identification, profile alignment and biomarker identification. Using Continuous Wavelet Transform (CWT), this package provides a reliable algorithm for peak detection that does not require any type of smoothing or previous baseline correction method, providing more consistent results for different spectra. See <doi:10.1093/bioinformatics/btl355} for further details.
Last updated 1 years ago
bioconductor-package
6 stars 3.26 score 0 dependencies 15 dependentsChemometricsWithR - Chemometrics with R - Multivariate Data Analysis in the Natural Sciences and Life Sciences (2nd Edition)
Functions and scripts used in the book "Chemometrics with R - Multivariate Data Analysis in the Natural Sciences and Life Sciences", 2nd edition, by Ron Wehrens, Springer (2019).
Last updated 4 years ago
13 stars 1.31 score 4 dependencies