Peak alignment software tools | Mass spectrometry-based untargeted metabolomics
Peak alignment procedures for samples from LC-MS and GC-MS (also CE-MS, MS, FT-MS, UV, NMR, MALDI) measurements play an important role during biomarker detection and metabolomic studies in general. As there is always a difference in the samples due to machine drift, samples need accurate correction to point to the same metabolite or component. Several packages have emerged since several years, some of them commercial, some of them free, some of them simple, some of them complex.
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.
A web-based tool that objectively quantifies every metabolite peak detected in a set of samples and aligns peaks across multiple samples to enable quantitative comparison of each metabolite between samples. The analysis incorporates quantification of multiple peaks/ions that have different chromatographic retention times but are detected within a single SRM transition.
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.
Aligns and calculates pairwise similarity scores among mass spectrometry (MS)/MS spectral data. MetCirc is an open-source package to make biological sense of mass spectral similarities from metabolomics data by providing a dedicated data analysis infrastructure and visualization interface to explore small molecules that mediate functionally important phenotypes. It can be used to pinpoint and formulate first structural hypothesis on previously non-characterized metabolites associated with a given phenotype.
Allows Next Generation Sequencing (NGS), microarray analysis, mass spectrometry, and gene ontology. Bioinformatics Toolbox deals with genomic and proteomic information and furnishes functions to explore and display this data with sequence browsers, spatial heatmaps, and clustergrams. It can find peaks, impute values for missing data, and select features using statistical techniques.
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