LFQuant 20120114 – Label-free Quantitative Analysis Tool for LC-MS/MS Proteomics Data

LFQuant 20120114

:: DESCRIPTION

LFQuant is a new analysis tool for label-free LC-MS/MS quantitative proteomics data. It is compatible with high-resolution mass spectrometers (Thermo RAW data) and two popular database search engines (SEQUEST and MASCOT) with target-decoy search strategy.

::DEVELOPER

LFQuant team

:: SCREENSHOTS

LFQuant

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

 LFQuant

:: MORE INFORMATION

Citation

Proteomics. 2012 Dec;12(23-24):3475-84. doi: 10.1002/pmic.201200017.
LFQuant: a label-free fast quantitative analysis tool for high-resolution LC-MS/MS proteomics data.
Zhang W1, Zhang J, Xu C, Li N, Liu H, Ma J, Zhu Y, Xie H.

aLFQ 1.3.6 – Estimating Absolute Protein Quantities from Label-free LC-MS/MS Proteomics data

aLFQ 1.3.6

:: DESCRIPTION

aLFQ is a bioinformatics tool which supports the commonly used absolute label-free protein abundance estimation methods (TopN, iBAQ, APEX, NSAF and SCAMPI) for LC-MS/MS proteomics data, together with validation algorithms enabling automated data analysis and error estimation.

::DEVELOPER

aLFQ team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • R

:: DOWNLOAD

 aLFQ

:: MORE INFORMATION

Citation

aLFQ: an R-package for estimating absolute protein quantities from label-free LC-MS/MS proteomics data.
Rosenberger G, Ludwig C, Röst HL, Aebersold R, Malmström L.
Bioinformatics. 2014 Sep 1;30(17):2511-3. doi: 10.1093/bioinformatics/btu200.

OpenMS / pyOpenMS 2.6.0 – C++ / Python Framework for Proteomics

OpenMS / pyOpenMS 2.6.0

:: DESCRIPTION

OpenMS is an open-source software C++ library for LC/MS data management and analyses. It offers an infrastructure for the development of mass spectrometry related software.

pyOpenMS provides Python-bindings for the C++ OpenMS mass spectrometric algorithm library, allowing researchers to directly access algorithms and data structures available in C++ from the interactive Python environment. pyOpenMS thus provides access to a feature-rich, open-source algorithm library for mass-spectrometry based proteomics analysis, giving the user functionality ranging from file access (mzXML, mzML, TraML, mzIdentML among others), basic signal processing (smoothing, filtering, de-isotoping and peak-picking) and complex data analysis (including label-free, SILAC, iTRAQ and SWATH analysis tools).

DEVELOPER

OpenMS Team

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux/ Windows  / MacOsX
  • C++ Compiler / Python

:: DOWNLOAD

 OpenMS / pyOpenMS

:: MORE INFORMATION

Citation:

Röst HL, Schmitt U, Aebersold R, Malmström L.
pyOpenMS: a Python-based interface to the OpenMS mass-spectrometry algorithm library.
Proteomics. 2014 Jan;14(1):74-7. doi: 10.1002/pmic.201300246. PMID: 24420968.

TOPPAS: A Graphical Workflow Editor for the Analysis of High-Throughput Proteomics Data.
Junker J, Bielow C, Bertsch A, Sturm M, Reinert K, Kohlbacher O.
J Proteome Res. 2012 Jul 6;11(7):3914-20. Epub 2012 May 24.

OpenMS and TOPP: open source software for LC-MS data analysis.
Bertsch A, Gröpl C, Reinert K, Kohlbacher O.
Methods Mol Biol. 2011;696:353-67.

Sipros 3.0 – Proteomics Data Analysis software

Sipros 3.0

:: DESCRIPTION

Sipros is a database-searching algorithm for peptide and protein identification in shotgun proteomics.

:: DESCRIPTION

the Pan lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux
  • Python
  • R package

:: DOWNLOAD

 Sipros

:: MORE INFORMATION

Citation

Sipros/ProRata: a versatile informatics system for quantitative community proteomics.
Wang Y, Ahn TH, Li Z, Pan C.
Bioinformatics. 2013 Aug 15;29(16):2064-5. doi: 10.1093/bioinformatics/btt329.

CIG-P 1.1 – Circular Interaction Graph for Proteomics

CIG-P 1.1

:: DESCRIPTION

CIG-P is a higher order visualization tool for AP-MS which generates intuitive circular diagrams for visually appealing final representation of AP-MS data.

::DEVELOPER

CIG-P team

:: SCREENSHOTS

CIG-P

:: REQUIREMENTS

  • Linux / Windows/ MacOsX

:: DOWNLOAD

 CIG-P

:: MORE INFORMATION

Citation:

BMC Bioinformatics. 2014 Oct 31;15:344. doi: 10.1186/1471-2105-15-344.
CIG-P: Circular Interaction Graph for Proteomics.
Hobbs CK, Leung M, Tsang HH1, Ebhardt HA.

ProtViz 0.6.8 – Proteomics Data Analysis & Visualization

ProtViz 0.6.8

:: DESCRIPTION

protViz is an R package that helps with quality checks, vizualizations and analysis of mass spectrometry data, coming from proteomics experiments. The package is developed, tested and used at the Functional Genomics Center Zurich. We use this package mainly for prototyping, teaching, and having fun with proteomics data. But it can also be used to do solid data analysis for small scale data sets.

::DEVELOPER

The Functional Genomics Center Zurich (FGCZ)

:: SCREENSHOTS

n/a

::REQUIREMENTS

  • Linux / Solaris / MacOS X
  • R package

:: DOWNLOAD

 ProtViz

:: MORE INFORMATION

EBprot 1.1.1 – Bayesian Analysis of labeling-based Quantitative Proteomics Data

EBprot 1.1.1

:: DESCRIPTION

EBprot is a novel probabilistic framework that directly models the peptide-protein hierarchy and rewards the proteins with reproducible evidence of DE over multiple peptides.

::DEVELOPER

EBprot team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Mac OsX / Windows
  • R

:: DOWNLOAD

 EBprot

:: MORE INFORMATION

Citation

EBprot: Statistical analysis of labeling-based quantitative proteomics data.
Koh HW, Swa HL, Fermin D, Ler SG, Gunaratne J, Choi H.
Proteomics. 2015 Aug;15(15):2580-91. doi: 10.1002/pmic.201400620.

Compomics-utilities 5.0.9 – Java Library encompassing shared code of various Proteomics research projects

Compomics-utilities 5.0.9

:: DESCRIPTION

Compomics-utilities is an open-source support library for computational proteomics. The library contains a broad set of features required for reading, parsing, and analyzing proteomics data. compomics-utilities is already used by a long list of existing software, ensuring library stability and continued support and development.

::DEVELOPER

The Proteomics Unit at the University of Bergen (PROBE)

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • Java

:: DOWNLOAD

 Compomics-utilities

:: MORE INFORMATION

Citation

Barsnes et al:
compomics-utilities: an open-source Java library for computational proteomics.
BMC Bioinformatics. 2011 Mar 8;12(1):70.

Pyteomics 4.4.2 – Python Framework for Exploratory Data Analysis and Rapid Software Prototyping in Proteomics

Pyteomics 4.4.2

:: DESCRIPTION

Pyteomics is a collection of lightweight and handy tools for Python that help to handle various sorts of proteomics data. Pyteomics provides a growing set of modules to facilitate the most common tasks in proteomics data analysis

::DEVELOPER

Pyteomics team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOSX
  • Python

:: DOWNLOAD

 Pyteomics

:: MORE INFORMATION

Citation

Goloborodko, A.A.; Levitsky, L.I.; Ivanov, M.V.; and Gorshkov, M.V. (2013)
Pyteomics – a Python Framework for Exploratory Data Analysis and Rapid Software Prototyping in Proteomics”,
Journal of The American Society for Mass Spectrometry, 24(2), 301–304. DOI: 10.1007/s13361-012-0516-6

specL 1.26.0 – Prepare Peptide Spectrum Matches for Use in Targeted Proteomics

specL 1.26.0

:: DESCRIPTION

specL provides a function for generating spectra libraries which can be used for MRM SRM MS workflows in proteomics. The package provides a BiblioSpec reader, a function which can add the protein information using a FASTA formatted amino acid file, and an export method for using the created library in the Spectronaut software.

::DEVELOPER

specL team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/ Linux /MacOsX
  • R/Bioconductor

:: DOWNLOAD

 specL

:: MORE INFORMATION

Citation:

specL – An R/Bioconductor package to prepare peptide spectrum matches for use in targeted proteomics.
Panse C, Trachsel C, Grossmann J, Schlapbach R.
Bioinformatics. 2015 Feb 23. pii: btv105.