Automated reprocessing pipeline for searching heterogeneous mass spectrometric data of the HUPO Brain Proteome Project pilot phase.
The newly available techniques for sensitive proteome analysis and the resulting amount of data require a new bioinformatics focus on automatic methods for spectrum reprocessing and peptide/protein validation. Manual validation of results in such studies is not feasible and objective enough for quality relevant interpretation. The necessity for tools enabling an automatic quality control is, therefore, important to produce reliable and comparable data in such big consortia as the Human Proteome Organization Brain Proteome Project. Standards and well-defined processing pipelines are important for these consortia. We show a way for choosing the right database model, through collecting data, processing these with a decoy database and end up with a quality controlled protein list merged from several search engines, including a known false-positive rate.
Stephan
Christian
C
Medizinisches Proteom-Center, Ruhr-Universität Bochum, Bochum, Germany. Christian.Stephan@rub.de
Reidegeld
Kai A
KA
Hamacher
Michael
M
van Hall
André
A
Marcus
Katrin
K
Taylor
Chris
C
Jones
Philip
P
Müller
Michael
M
Apweiler
Rolf
R
Martens
Lennart
L
Körting
Gerhard
G
Chamrad
Daniel C
DC
Thiele
Herbert
H
Blüggel
Martin
M
Parkinson
David
D
Binz
Pierre-Alain
PA
Lyall
Andrew
A
Meyer
Helmut E
HE
D000465:Algorithms; D001921:Brain / Q000378:metabolism*; D019295:Computational Biology; D030562:Databases, Protein; D006801:Humans; D016247:Information Storage and Retrieval; D013058:Mass Spectrometry; D015337:Multicenter Studies as Topic; D010865:Pilot Projects; D020543:Proteome / Q000032:analysis* / Q000378:metabolism
D020543:Proteome