TY - JOUR
T1 - SILACAnalyzer - A tool for differential quantitaion of stable isotope derived data
AU - Nilse, Lars
AU - Sturm, Marc
AU - Trudgian, David
AU - Salek, Mogjiborahman
AU - Sims, Paul F. G.
AU - Carroll, Kathleen M.
AU - Hubbard, Simon J.
PY - 2010
Y1 - 2010
N2 - Abstract. Quantitative proteomics is a growing field where several experimentaltechniques such as those based around stable isotope labellingare reaching maturity. These advances require the parallel developmentof informatics tools to process and analyse the data, especially for highthroughputexperiments seeking to quantify large numbers of proteins.We have developed a novel algorithm for the quantitative analysis of stableisotope-based proteomics data at the peptide level. Without prior formalidentification of the peptides by MS/MS, the algorithm determinesthe mass charge ratio m/z and retention time t of stable isotope-labelledpeptide pairs and calculates their relative ratios. It supports several nonproprietaryXML input formats and requires only minimal parametertuning and runs fully automated. We have tested its performance on alow complexity peptide sample in an initial study. In comparison to amanual analysis and an automated approach using MSQuant, it performsas well or better and therefore we believe it has utility for groups wishingto perform high-throughput experiments.
AB - Abstract. Quantitative proteomics is a growing field where several experimentaltechniques such as those based around stable isotope labellingare reaching maturity. These advances require the parallel developmentof informatics tools to process and analyse the data, especially for highthroughputexperiments seeking to quantify large numbers of proteins.We have developed a novel algorithm for the quantitative analysis of stableisotope-based proteomics data at the peptide level. Without prior formalidentification of the peptides by MS/MS, the algorithm determinesthe mass charge ratio m/z and retention time t of stable isotope-labelledpeptide pairs and calculates their relative ratios. It supports several nonproprietaryXML input formats and requires only minimal parametertuning and runs fully automated. We have tested its performance on alow complexity peptide sample in an initial study. In comparison to amanual analysis and an automated approach using MSQuant, it performsas well or better and therefore we believe it has utility for groups wishingto perform high-throughput experiments.
U2 - DOI: 10.1007/978-3-642-14571-1
DO - DOI: 10.1007/978-3-642-14571-1
M3 - Article
SN - 0302-9743
VL - 6160
SP - 45
EP - 55
JO - Lecture Notes in Computer Science
JF - Lecture Notes in Computer Science
IS - 1
ER -