Showing 5 of total 5 results (show query)
bioc
xcms:LC-MS and GC-MS Data Analysis
Framework for processing and visualization of chromatographically separated and single-spectra mass spectral data. Imports from AIA/ANDI NetCDF, mzXML, mzData and mzML files. Preprocesses data for high-throughput, untargeted analyte profiling.
Maintained by Steffen Neumann. Last updated 15 days ago.
immunooncologymassspectrometrymetabolomicsbioconductorfeature-detectionmass-spectrometrypeak-detectioncpp
196 stars 14.31 score 984 scripts 11 dependentsbioc
nucleR:Nucleosome positioning package for R
Nucleosome positioning for Tiling Arrays and NGS experiments.
Maintained by Alba Sala. Last updated 5 months ago.
nucleosomepositioningcoveragechipseqmicroarraysequencinggeneticsqualitycontroldataimport
5.32 score 21 scriptsbioc
CNAnorm:A normalization method for Copy Number Aberration in cancer samples
Performs ratio, GC content correction and normalization of data obtained using low coverage (one read every 100-10,000 bp) high troughput sequencing. It performs a "discrete" normalization looking for the ploidy of the genome. It will also provide tumour content if at least two ploidy states can be found.
Maintained by Stefano Berri. Last updated 5 months ago.
copynumbervariationsequencingcoveragenormalizationwholegenomednaseqgenomicvariationfortran
4.30 score 6 scripts
noemiallefs
andurinha:Make Spectroscopic Data Processing Easier
The goal of 'andurinha' is provide a fast and friendly way to process spectroscopic data. It is intended for processing several spectra of samples with similar composition (tens to hundreds of spectra). It compiles spectroscopy data files, produces standardized and second derivative spectra, finds peaks and allows to select the most significant ones based on the second derivative/absorbance sum spectrum. It also provides functions for graphic evaluation of the outputs.
Maintained by Noemi Alvarez Fernandez. Last updated 2 years ago.
peakspeaks-selectionspectroscopy
1 stars 3.70 score 6 scripts
cran
MGBT:Multiple Grubbs-Beck Low-Outlier Test
Compute the multiple Grubbs-Beck low-outlier test on positively distributed data and utilities for noninterpretive U.S. Geological Survey annual peak-streamflow data processing discussed in Cohn et al. (2013) <doi:10.1002/wrcr.20392> and England et al. (2017) <doi:10.3133/tm4B5>.
Maintained by William H. Asquith. Last updated 4 years ago.
1 stars 1.70 score