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.

PeakLink 1.0 – Peptide Peak Linking method in LC-MS/MS using Wavelet and SVM

PeakLink 1.0

:: DESCRIPTION

PeakLink (PL) uses information in both the time and frequency domain as inputs to a non-linear support vector machine (SVM) classifier. The PL algorithm first uses a threshold on retention time to remove candidate corresponding peaks with excessively large elution time shifts, then PL calculates the correlation between a pair of candidate peaks after removing noise through wavelet transformation. After converting retention time and peak shape correlation to statistical scores, an SVM classifier is trained and applied for differentiating corresponding and non-corresponding peptide peaks.

::DEVELOPER

PeakLink team

:: SCREENSHOTS

N/A

::REQUIREMENTS

Linux / Windows / MacOsX
MatLab

:: DOWNLOAD

PeakLink

:: MORE INFORMATION

Citation

Bioinformatics. 2014 Sep 1;30(17):2464-70. doi: 10.1093/bioinformatics/btu299. Epub 2014 May 9.
PeakLink: a new peptide peak linking method in LC-MS/MS using wavelet and SVM.
Ghanat Bari M, Ma X, Zhang J.

MSBayesPro – Bayesian Protein Inference for LC-MS/MS Proteomics experiment

MSBayesPro

:: DESCRIPTION

MSBayesPro is a software package and web tool for Bayesian protein inference from tandem mass spectrometry peptide identifications. It uses a set of identified peptides (or peptides with scores in a MS/MS search), peptide detectability, and a protein database to provide probabilities of protein identifications.

::DEVELOPER

Yong Fuga Li

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux/ Windows

:: DOWNLOAD

MSBayesPro

:: MORE INFORMATION

Citation

J Comput Biol. 2009 Aug;16(8):1183-93. doi: 10.1089/cmb.2009.0018.
A bayesian approach to protein inference problem in shotgun proteomics.
Li YF1, Arnold RJ, Li Y, Radivojac P, Sheng Q, Tang H.