Literature DB >> 25938255

PIA: An Intuitive Protein Inference Engine with a Web-Based User Interface.

Julian Uszkoreit1, Alexandra Maerkens1, Yasset Perez-Riverol1, Helmut E Meyer1, Katrin Marcus1, Christian Stephan1, Oliver Kohlbacher1, Martin Eisenacher1.   

Abstract

Protein inference connects the peptide spectrum matches (PSMs) obtained from database search engines back to proteins, which are typically at the heart of most proteomics studies. Different search engines yield different PSMs and thus different protein lists. Analysis of results from one or multiple search engines is often hampered by different data exchange formats and lack of convenient and intuitive user interfaces. We present PIA, a flexible software suite for combining PSMs from different search engine runs and turning these into consistent results. PIA can be integrated into proteomics data analysis workflows in several ways. A user-friendly graphical user interface can be run either locally or (e.g., for larger core facilities) from a central server. For automated data processing, stand-alone tools are available. PIA implements several established protein inference algorithms and can combine results from different search engines seamlessly. On several benchmark data sets, we show that PIA can identify a larger number of proteins at the same protein FDR when compared to that using inference based on a single search engine. PIA supports the majority of established search engines and data in the mzIdentML standard format. It is implemented in Java and freely available at https://github.com/mpc-bioinformatics/pia.

Entities:  

Keywords:  Protein inference; database search; identification analysis; mass spectrometry; peptide identification; protein identification; search engine combination

Mesh:

Substances:

Year:  2015        PMID: 25938255     DOI: 10.1021/acs.jproteome.5b00121

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  27 in total

1.  Param-Medic: A Tool for Improving MS/MS Database Search Yield by Optimizing Parameter Settings.

Authors:  Damon H May; Kaipo Tamura; William S Noble
Journal:  J Proteome Res       Date:  2017-03-13       Impact factor: 4.466

2.  Proteomics of rimmed vacuoles define new risk allele in inclusion body myositis.

Authors:  Anne-Katrin Güttsches; Stefen Brady; Kathryn Krause; Alexandra Maerkens; Julian Uszkoreit; Martin Eisenacher; Anja Schreiner; Sara Galozzi; Janine Mertens-Rill; Martin Tegenthoff; Janice L Holton; Matthew B Harms; Thomas E Lloyd; Matthias Vorgerd; Conrad C Weihl; Katrin Marcus; Rudolf A Kley
Journal:  Ann Neurol       Date:  2017-01-27       Impact factor: 10.422

3.  Dataset containing physiological amounts of spike-in proteins into murine C2C12 background as a ground truth quantitative LC-MS/MS reference.

Authors:  Julian Uszkoreit; Katalin Barkovits; Sandra Pacharra; Kathy Pfeiffer; Simone Steinbach; Katrin Marcus; Martin Eisenacher
Journal:  Data Brief       Date:  2022-07-04

4.  Characterization of peptide-protein relationships in protein ambiguity groups via bipartite graphs.

Authors:  Karin Schork; Michael Turewicz; Julian Uszkoreit; Jörg Rahnenführer; Martin Eisenacher
Journal:  PLoS One       Date:  2022-10-21       Impact factor: 3.752

5.  EPIFANY: A Method for Efficient High-Confidence Protein Inference.

Authors:  Julianus Pfeuffer; Timo Sachsenberg; Tjeerd M H Dijkstra; Oliver Serang; Knut Reinert; Oliver Kohlbacher
Journal:  J Proteome Res       Date:  2020-02-13       Impact factor: 4.466

6.  A Protein Standard That Emulates Homology for the Characterization of Protein Inference Algorithms.

Authors:  Matthew The; Fredrik Edfors; Yasset Perez-Riverol; Samuel H Payne; Michael R Hoopmann; Magnus Palmblad; Björn Forsström; Lukas Käll
Journal:  J Proteome Res       Date:  2018-04-16       Impact factor: 4.466

Review 7.  Scalable Data Analysis in Proteomics and Metabolomics Using BioContainers and Workflows Engines.

Authors:  Yasset Perez-Riverol; Pablo Moreno
Journal:  Proteomics       Date:  2019-12-18       Impact factor: 5.393

8.  Transcriptome and Proteome Analysis in LUHMES Cells Overexpressing Alpha-Synuclein.

Authors:  Matthias Höllerhage; Markus Stepath; Michael Kohl; Kathy Pfeiffer; Oscar Wing Ho Chua; Linghan Duan; Franziska Hopfner; Martin Eisenacher; Katrin Marcus; Günter U Höglinger
Journal:  Front Neurol       Date:  2022-04-11       Impact factor: 4.003

9.  PRIDE Inspector Toolsuite: Moving Toward a Universal Visualization Tool for Proteomics Data Standard Formats and Quality Assessment of ProteomeXchange Datasets.

Authors:  Yasset Perez-Riverol; Qing-Wei Xu; Rui Wang; Julian Uszkoreit; Johannes Griss; Aniel Sanchez; Florian Reisinger; Attila Csordas; Tobias Ternent; Noemi Del-Toro; Jose A Dianes; Martin Eisenacher; Henning Hermjakob; Juan Antonio Vizcaíno
Journal:  Mol Cell Proteomics       Date:  2015-11-06       Impact factor: 5.911

10.  New insights into the protein aggregation pathology in myotilinopathy by combined proteomic and immunolocalization analyses.

Authors:  A Maerkens; M Olivé; A Schreiner; S Feldkirchner; J Schessl; J Uszkoreit; K Barkovits; A K Güttsches; V Theis; M Eisenacher; M Tegenthoff; L G Goldfarb; R Schröder; B Schoser; P F M van der Ven; D O Fürst; M Vorgerd; K Marcus; R A Kley
Journal:  Acta Neuropathol Commun       Date:  2016-02-03       Impact factor: 7.801

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