DISCO

DISCO (distance and spectrum correlation optimization) software was developed to algin peak lists of two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC/TOF-MS) data. This algorithm uses the output of the instrument control software, ChromaTOF, as its input data. It detects and merges multiple peak entries of the same metabolite into one peak entry in each input peak list. After a z-score transformation of metabolite retention times, DISCO selects landmark peaks from all samples based on both two-dimensional retention times and mass spectrum similarity of fragment ions measured by Pearson’s correlation coefficient. A local linear fitting method is employed in the original two-dimensional retention time space to correct retention time shifts. A progressive retention time map searching method is used to align metabolite peaks in all samples together based on optimization of the Euclidean distance and mass spectrum similarity.

Citation of this software. Wang, B.; Fang, A.; Heim, J.; Bogdanov, B.; Pugh, S.; Libardoni, M.; Zhang, X. DISCO: distance and spectrum correlation optimization alignment for two dimensional gas chromatography time-of-flight mass spectrometry - based metabolomics. Anal. Chem. 2010, 82, 5069-5081.

SysNet

SysNet is an interactive visual data mining application thatprovides an interactive environment for the analysis of high data volume molecular expression information of most any type from biological systems. It integrates interactive graphic visualization and statistical data mining into a single package. SysNet interactively presents intermolecular correlation information with circular and heatmap layouts. It is also applicable to comparative analysis of molecular expression data, such as time lapse data.

Citation of this software. Zhang, M.; Ouyang, Q.; Stephenson, A.; Kane, M. D.; Salt, D. E.; Prabhakar, S.; Buck, C.;  Zhang, X. Interactive analysis of ‘omics molecular expression data. BMC Systems Biology 2008, 2:23.

MSort

MSort is a peak sorting method for the two-dimensional gas chromatography/time-of-flight mass spectrometry (GC´GC/TOF-MS) system. The objective of peak sorting is to recognize peaks from the same metabolite occurring in different samples from thousands of peaks detected in the analytical procedure. Raw instrument data are first processed by ChromaTOF(Leco) software to provide the peak tables. MSort achieves peak sorting by utilizing the first and second dimension retention times in the peak tables and the mass spectra generated during the process of electron ionization.

Citation of this software. Oh, C.; Huang, X.; Buck, C.; Regnier, E. F.; Zhang, X. Comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry peak sorting algorithm. J. Chromatogr. A 2008, 1179, 205-215.

XMass

XMass was designed to analyze LC-MS data only. It was modified based on GISTool software written by Xiang Zhang et al. (2005) and can be run on a Window system. This software was designed as a component of data analysis pipeline for protein biomarker discovery. Therefore, no user interface is provided. There were several functionalities have been updated compared with GISTool, such as centrolizing profile data, calculation of resolution between two paired peaks, more generic design for representing stable isotope labeling methods, accepting multiple data formats.

Citation of this software. Zhang, X.; Hines, W.; Adamec, J.; Asara, J.; Naylor, S.; and Regnier, F. E. An automated method for the analysis of stable isotope labeling data for proteomics. J. Am. Soc. Mass Spectrom. 2005, 16, 1181-1191.

XAlign

XAlign is a Windows-based software used for recognizing peaks that have been generated by the same peptide but which can be detected in different samples in the course of LC-MS experiments. This software is designed as a component of the data analysis pipeline for protein biomarker discovery; therefore, no user interface is provided. XAlign uses a two-step alignment algorithm: step one detects significant peaks that are common to all samples. An average peak serial is created based on the significant peaks. A sample with significant peaks that are closely similar to the average peak serial is defined as the median sample. Step two aligns all samples to the median sample using refined m/z and retention variation values, where pattern recognition is applied as needed.

Citation of this software. Zhang, X.; Asara, J. M.; Adamec, J.; Ouzzani, M.; and Elmagarmid, A. K. Data preprocessing in liquid chromatography-mass spectrometry based proteomics. Bioinformatics, 2005, 21, 4054-4059.