Peak alignment software tools | Mass spectrometry-based untargeted proteomics
Liquid chromatography-mass spectrometry is widely used for comparative replicate sample analysis in proteomics, lipidomics and metabolomics. Before statistical comparison, registration must be established to match corresponding analytes from run to run. Alignment, the most popular correspondence approach, consists of constructing a function that warps the content of runs to most closely match a given reference sample.
Allows to manage and analyse Liquid chromatography coupled to mass spectrometry (LC-MS) data. OpenMS is a programming library and tool collection integrated into full-featured workflow systems, such as KNIME, Galaxy and WS-PGRADE, to facilitate bioinformatics research in the field of MS on all levels. The software provides pre-built and ready-to-use tools for analysis of both proteomics and non-targeted metabolomics data.
An LC/MS-based data analysis approach which incorporates novel nonlinear retention time alignment, feature detection, and feature matching. The XCMS software reads and processes LC/MS data stored in netcdf , mzXML, mzData and mzML files. It provides methods for feature detection, non-linear retention time alignment, visualization, relative quantization and statistics. XCMS is capable of simultaneously preprocessing, analyzing, and visualizing the raw data from hundreds of samples. XCMS is freely available under an open-source license.
An open-source software tool for mass-spectrometry data processing, with the main focus on LC-MS data. It is based on the original MZmine toolbox described in the 2006 Bioinformatics publication, but has been completely redesigned and rewritten since then. Our main goal is to provide a user-friendly, flexible and easily extendable software with a complete set of modules covering the entire LC-MS data analysis workflow.
Aims to put corresponding features at the same locations. The algorithm searches for an optimal polynomial describing the warping. It is possible to align one sample to a reference, several samples to the same reference, or several samples to several references. One can choose between calculating individual warpings, or one global warping for a set of samples and one reference. Two optimization criteria are implemented: RMS (Root Mean Square error) and WCC (Weighted Cross Correlation).
A package for the registration of either chromatograms or peak lists. AMSRPM implements a variant of the Robust Point Matching algorithm that is tailored for the alignment of LC and LC/MS experiments. The algorithm does not rely on pre-specified landmarks, it is insensitive towards outliers and capable of modeling nonlinear distortions. The main limitation of amsrpm currently is the computational burden involved in repetitively calculating the distance matrix and the smooth monotone regression estimate.
Allows to view mass spectrometry (MS1) data in an mzXML file. msInspect is An open-source application comprising algorithms and visualization tools for the analysis of multiple LC-MS experimental measurements. It can be used to built-in tools to inspect data, identify peptide features, generate peptide arrays using data from multiple runs, and export data to external applications for further analysis and collaboration. It offers also a full Accurate Mass and Time (AMT) workflow for combining LC-MS and LC-MS/MS peptides.
An R package providing a complete and modular analysis pipeline for quantitative analysis of mass spectrometry data. MALDIquant is specifically designed with application in clinical diagnostics in mind and implements sophisticated routines for importing raw data, preprocessing, non-linear peak alignment and calibration. It also handles technical replicates as well as spectra with unequal resolution.
Permits a linear and non-linear retention time (rt) alignment of peak-picked data in liquid chromatography and mass spectrometry (LC/MS) runs. Many alignment methods have been proposed in the literature and each of them need huge amounts of computer memory due to the size of the input data, thus making it impractical the analyse of hundreds of runs. This procedure of alignment seems to be highly competitive compared to many other available algorithms.
Analyzes metabolomics data generated from the 2D gas chromatography time-of-flight mass spectrometry (GCxGC-TOF MS) instrument. MetPP is able to recognize the concentration difference of the spiked-in metabolite standards between sample groups. It is composed of different modules for: retention index matching, peak filtering and merging, peak list alignment, quant mass conversion, normalization, statistical significance tests and pattern recognition.
Combines hierarchical pairwise correspondence estimation with simultaneous alignment and global retention time correction. SIMA employs a tailored multidimensional kernel function and a procedure based on maximum likelihood estimation to find the retention time distortion function that best fits the observed data. In a comparison with seven alternative methods on four different datasets, SIMA yields competitive and superior performance on real-world data. Conceptually, SIMA is not limited to the alignment of LC/MS data: by redefinition of the thresholded squared Mahalanobis distance function, it can easily be adapted to any time series with discrete events
Allows alignment of homogeneous data. mSPA is especially designed for two-dimensional gas chromatography mass spectrometry (GC × GC–MS). It employs the peak distance and the spectra similarity sequentially in parallel to proceed. This tool was tested on two sets of GC × GC–MS data. The results show that the Canberra distance is able to make good performances and the proposed mixture similarity peak alignment algorithm prevailed against all literature reported methods.
A Bayesian alignment model for LC-MS data analysis. AlignLCMS provides estimates of the RT variability along with uncertainty measures. The model enables integration of multiple sources of information including internal standards and clustered chromatograms in a mathematically rigorous framework. It improves significantly the RT alignment performance through appropriate integration of relevant information.
An algorithm based on weighted bipartite matching. Unlike existing tools, which search for accurate warping functions to correct chromatographic retention time shifts, it directly seeks a peak-to-peak mapping by maximizing a global similarity function between two LC-MS maps.
Uses information in both the time and frequency domain as inputs to a non-linear support vector machine classifier. PeakLink offers the highest accuracy in various challenging test cases including complex samples from different tissues, different instruments and different laboratories. The proposed method could have wide applications in biological and clinical studies when protein expression changes across different conditions need examination.
A direct matching peak alignment method for LC/MS data that incorporates related peaks information (within each LC/MS run) and investigate its effect on alignment performance (across runs). The groupings of related peaks necessary for this method can be obtained from any peak clustering method and are built into a pairwise peak similarity score function. The similarity score matrix produced is used by an approximation algorithm for the weighted matching problem to produce the actual alignment result.
Conducts alignments for two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC/TOF-MS)-based metabolomics. DISCO uses Euclidean distances of two-dimensional retention times and mass spectrum correlation of two corresponding metabolite peaks. It can correct the two-dimensional retention time shifts of all metabolite peaks present in each peak list using a two-step approach. This tool is useful for pattern recognition and statistical significance testing in metabolomics study.
Performs retention time alignment on set of peaks. CowCoDA combines mass chromatogram selection using CODA with a modified COW algorithm in order to take the local information in Liquid Chromatography-Mass Spectrometry (LC-MS) chromatograms into account. The performance of the COW-CODA algorithm was evaluated on three types of complex data sets obtained from the LC-MS analysis of samples commonly used for biomarker discovery. CowCoDA is also applicable to high-resolution data using Gaussian smoothing and data reduction in mass dimension.
Performs a preliminary data comparison matrix of chemical data obtained by gas chromatography (GC) without mass spectrometry (MS) information. GCAligner is a computer program based on the comparison between the retention times of each detected compound in a sample. This software is a useful, simple and free program based on an algorithm that enables the alignment of table-type data from GC. The aim of GCALIGNER is to perform a first preliminary alignment on large datasets.