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.
A proteomics software that allows analysis of LC-MS/MS DIA (data independent acquisition) data. OpenSWATH was designed and optimized to work with profile data. While the software will run on centroided data, depending on the pre-processing applied, the quality of the chromatograms suffers and the results will be of lower quality.
A freely-available and open source Windows client application for building selected reaction monitoring (SRM)/multiple reaction monitoring (MRM), parallel reaction monitoring (PRM - targeted MS/MS), data independent acquisition (DIA/SWATH) and targeted DDA with MS1 quantitative methods and analyzing the resulting mass spectrometer data. Skyline aims to employ cutting-edge technologies for creating and iteratively refining targeted methods for large-scale proteomics studies.
An alignment software for targeted proteomics (SRM or SWATH-MS) data. TRIC uses a graph-based alignment strategy based on non-linear retention time correction to integrate information from all available runs. The input consists of a set of csv files derived from a targeted proteomics experiment generated by OpenSWATH (using either mProphet or pyProphet) or generated by Peakview.
Provides an automated method of objectively evaluating MRM-MS data to identify inaccurate transition data based on the presence of interfering signal or inconsistent recovery between replicate samples.
An R package for statistical relative quantification of proteins and peptides in mass spectrometry-based proteomics. Version 2.0 of MSstats supports label-free and label-based experimental workflows and data-dependent, targeted and data-independent spectral acquisition. It takes as input identified and quantified spectral peaks, and outputs a list of differentially abundant peptides or proteins, or summaries of peptide or protein relative abundance. MSstats relies on a flexible family of linear mixed models.
Analyzes data-independent acquisition (DIA) mass spectrometry (MS) data with precursor ion assays of a spectral library. SWATHProphet can detect fragment ion interferences. They can be removed either by reanalysis after their substitution for non-interfering ions in the library or in silico by adjustment of peak group quantitation, scores, and computed probabilities. The tool is able to analyze documents discrepancies between libraries and observe peak intensities.
Analyses high-resolution LC-MS/MS proteomics data based on database searching. LFQuant can handle large-scale label-free data with fractionation such as SDS-PAGE and 2D LC. It is easy to use and provides handy user interfaces for data loading, parameter setting, quantitative analysis, and quantitative data visualization. LFQuant performs better than MaxQuant and IDEAL-Q, two common quantification software packages, in terms of both precision and accuracy, and consumes significantly less processing time.
A software package for statistical analysis of differential protein expression using DIA fragment-level intensities. The workflow consists of three major steps: intensity normalization, peptide/fragment selection, and statistical analysis. First, mapDIA offers normalization of fragment-level intensities by total intensity sums as well as a novel alternative normalization by local intensity sums in retention time space. Second, mapDIA removes outlier observations and selects peptides/fragments that preserve the major quantitative patterns across all samples for each protein. Last, using the selected fragments and peptides, mapDIA performs model-based statistical significance analysis of protein-level differential expression between specified groups of samples.
A package intended to transform SWATH data from the OpenSWATH software into a format readable by other statistics packages while performing filtering, annotation and FDR estimation. SWATH2stats allows to i) annotate the data, ii) analyze reproducibility across replicates, iii) estimate the FDR, iv) filter for assays meeting certain confidence or other criteria and v) convert the large proteomic datasets to the respective input formats of the downstream analysis tools MSstats, mapDIA, and aLFQ.
A stand-alone software application that is compatible with all SCIEX mass spectrometer systems for the quantitative review of LC/MS and MS/MS data. PeakView® enables exploration and interpretation of mass spectral data with tools for processing accurate mass data, structural interpretation, and batch analysis.
Professional software that enables fully automated, fast and accurate signal processing of SWATH and DIA data sets (HRM-MS). HRM-MS is the next generation targeted proteomics technology invented at Biognosys that enables reproducible and precise quantification of 1000s of proteins in a single instrument run with data independent acquisition (DIA).
Allows to manage highly complex multiple reaction monitoring mass spectrometry (MRM-MS) experiments. MRMer functions in an instrument-agnostic fashion using an updated standard of the mzXML format. The software automatically extracts and groups precursor-product pairs for visual validation of co-elution and calculates absolute and relative area under the curves (AUCs) for standard and absolute quantification/stable isotope labeling by amino acids in cell culture (AQUA/SILAC) type experiments, respectively. It also permits the quantitative analysis experiments including heavy and light isotopic peptide pairs.
Dr. Yashwanth Subbannayya obtained his M.Sc. degree in Medical Biochemistry from Manipal University. He qualified the competitive CSIR-UGC National Eligibility Test and joined the Institute of Bioinformatics, Bangalore as a UGC Junior Research Fellow. As part of his Ph.D. work, he studied the molecular mechanisms of gastric cancer in clinical specimens using quantitative proteomic technologies. This study, the results of which were published in Cancer Biology and Therapy, yielded a novel therapeutic target for gastric cancer- CAMKK2. Further, he also studied the serum proteome of gastric cancer patients and developed assays for potential markers using the revolutionary multiple reaction monitoring approach. The results of this study were published in Journal of Proteomics. In addition to his research work, he also trained extensively in sample preparation for mass spectrometry, fractionation techniques and gained expertise in quantitative proteomic techniques and data analysis. In addition, he also trained extensively in various validation platforms including immunohistochemsitry, multiple reaction monitoring and Western blot. He has also worked as a curator for several biological databases including NetPath, Human Protein Reference Database (HPRD) and Breast cancer database. His work in various research projects have yielded him 23 publications either as lead author or co-author in peer reviewed journals. He is a reviewer for the journal Proteomics.
Dr. Yashwanth Subbannayya joined the YU-IOB Center for Systems Biology and Molecular Medicine in June, 2015. During the initial period, his job consisted of assisting other personnel of the university in the establishment of YU-IOB Center for Systems Biology and Molecular Medicine. He was also involved in training of Ph.D. students in biological aspects. After the establishment of the center, he trained in cell culture techniques and metabolomics analysis. At YU-IOB CSBMM, he is studying the molecular mechanisms in various cancers including oral cancer. In addition, he is studying the molecular mechanisms as well as the metabolic constituents of traditional medicine formulations using mass spectrometry technologies. In June 2016, he convened the national symposium “Genomics in clinical practice: Future of precision medicine” held at Yenepoya University on June 1 and 2, 2016. The resource persons included 16 individuals from various academic organizations as well as industry. The symposium was attended by 218 participants from 24 institutions around India. He is a member of the Scientific Review Board of Yenepoya Research Centre where he facilitates timely scientific review of research projects.