Literature DB >> 21360675

Abacus: a computational tool for extracting and pre-processing spectral count data for label-free quantitative proteomic analysis.

Damian Fermin1, Venkatesha Basrur, Anastasia K Yocum, Alexey I Nesvizhskii.   

Abstract

We describe Abacus, a computational tool for extracting spectral counts from MS/MS data sets. The program aggregates data from multiple experiments, adjusts spectral counts to accurately account for peptides shared across multiple proteins, and performs common normalization steps. It can also output the spectral count data at the gene level, thus simplifying the integration and comparison between gene and protein expression data. Abacus is compatible with the widely used Trans-Proteomic Pipeline suite of tools and comes with a graphical user interface making it easy to interact with the program. The main aim of Abacus is to streamline the analysis of spectral count data by providing an automated, easy to use solution for extracting this information from proteomic data sets for subsequent, more sophisticated statistical analysis.
Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Year:  2011        PMID: 21360675      PMCID: PMC3113614          DOI: 10.1002/pmic.201000650

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  35 in total

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6.  PepC: proteomics software for identifying differentially expressed proteins based on spectral counting.

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Journal:  Proteomics       Date:  2010-03       Impact factor: 3.984

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  48 in total

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Journal:  Stem Cell Rev Rep       Date:  2012-03       Impact factor: 5.739

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3.  Analyzing protein-protein interactions from affinity purification-mass spectrometry data with SAINT.

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Journal:  Curr Protoc Bioinformatics       Date:  2012-09

Review 4.  Protein analysis by shotgun/bottom-up proteomics.

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5.  Statistically enhanced spectral counting approach to TCDD cardiac toxicity in the adult zebrafish heart.

Authors:  Jiang Zhang; Kevin A Lanham; Warren Heideman; Richard E Peterson; Lingjun Li
Journal:  J Proteome Res       Date:  2013-06-12       Impact factor: 4.466

6.  Architecture of the Saccharomyces cerevisiae SAGA transcription coactivator complex.

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Journal:  EMBO J       Date:  2014-09-12       Impact factor: 11.598

7.  Deciphering thylakoid sub-compartments using a mass spectrometry-based approach.

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Journal:  Mol Cell Proteomics       Date:  2014-05-28       Impact factor: 5.911

8.  Improvements in proteomic metrics of low abundance proteins through proteome equalization using ProteoMiner prior to MudPIT.

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Journal:  J Proteome Res       Date:  2011-06-24       Impact factor: 4.466

9.  ANPELA: analysis and performance assessment of the label-free quantification workflow for metaproteomic studies.

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10.  Chemoproteomic Profiling Uncovers CDK4-Mediated Phosphorylation of the Translational Suppressor 4E-BP1.

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