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NetWeAvers / Network Weighted Averages
An R package for analyzing groups of regulated proteins in a network context, e.g. as defined by clusters of protein-protein interactions. NetWeAvers provides a method for analyzing proteomics data integrated with biological networks. The method includes an algorithm for finding dense clusters of proteins and a permutation algorithm to calculate cluster P-values. Optional steps include summarizing quantified peptide values to single protein values and testing for differential expression, such that the data input can simply be a list of identified and quantified peaks.
Peptigram
Is dedicated to the visualization and comparison of peptides detected by Tandem mass spectrometry (MS/MS). The principal advantage of Peptigram is that it provides visualizations at both the protein and peptide level, allowing users to simultaneously visualize the peptide distributions of one or more samples of interest, mapped to their parent proteins. In this way rapid comparisons between samples can be made in terms of their peptide coverage and abundance. Moreover, Peptigram integrates and displays key sequence features from external databases and links with peptide analysis tools to offer the user a comprehensive peptide discovery resource.
THRASH / Thorough high resolution analysis of spectra by Horn
A fully automated computer algorithm that can be applied to complex mass spectra of peptides and proteins. THRASH uses a subtractive peak finding routine to locate possible isotopic clusters in the spectrum. The program should be generally applicable to classes of large molecules, including DNA and polymers. It also includes methods for calculating background noise levels, determining charge state using the Fourier-Transform/Patterson technique, calculating theoretical profiles, and for subsequent fitting with observed isotopic profiles.
OpenChrom
Provides extension points to enable built-in import capabilities for binary or textual instrument vendors’ data formats. OpenChrom is an extensible cross-platform open source software for the mass spectrometric analysis of chromatographic data. This application offers extension points that enable the implementation of different baseline detectors as well as peak detectors and integrators. An option to implement filters, used to increase the chromatographic quality, is also available.
SPA / Sparse Proteomics Analysis
Finds optimal feature vectors which are extremely sparse, allowing a highly accurate classification, and robust against noise. Sparse Proteomics Analysis (SPA) is an algorithm based on the theory of compressed sensing that allows us to identify a minimal discriminating set of features from mass spectrometry data-sets. Its performance is competitive with standard (and widely used) algorithms for analyzing proteomics data. This method is robust against random and systematic noise.
DIA-NN / Data-Independent Acquisition by Neural Networks
New
Assists in enhancing signal processing in data-independent acquisition (DIA)-data. DIA-NN introduces artificial neural nets and a quantification strategy. It implements all stages of DIA data processing in a single program, taking a set of raw data files as input and reporting quantitative values for precursor ions and protein groups. This method was developed to be useful for automated handling of data generated in large-scale experiments.
DrDMASS+
Allows analysis of mass spectral data based on multivariate analysis. DrDMASS+ performs four stages: (1) Peak Correction that allows correction of experimental m/z values, (2) Multivariate Data Processing that permits assessment of reproducibility of samples with iterative measurement, and selection of useful peaks to separate groups of samples, (3) Unsupervised Learning that allows visualization of multivariate data and (4) Supervised Learning to obtain the regression equation.
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