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Workflow for analysis of high mass accuracy salivary data set using M ax Q uant and P rotein P ilot search algorithm
Author(s) -
Jagtap Pratik,
Bandhakavi Sricharan,
Higgins LeeAnn,
McGowan Thomas,
Sa Rongxiao,
Stone Matthew D.,
Chilton John,
Arriaga Edgar A.,
Seymour Sean L.,
Griffin Timothy J.
Publication year - 2012
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.201100097
Subject(s) - pipeline (software) , workflow , set (abstract data type) , data set , algorithm , identification (biology) , computer science , chromatography , chemistry , artificial intelligence , biology , database , botany , programming language
LTQ O rbitrap data analyzed with P rotein P ilot can be further improved by M ax Q uant raw data processing, which utilizes precursor‐level high mass accuracy data for peak processing and MGF creation. In particular, P rotein P ilot results from M ax Q uant‐processed peaklists for O rbitrap data sets resulted in improved spectral utilization due to an improved peaklist quality with higher precision and high precursor mass accuracy ( HPMA ). The output and postsearch analysis tools of both workflows were utilized for previously unexplored features of a three‐dimensional fractionated and hexapeptide library ( P roteo M iner) treated whole saliva data set comprising 200 fractions. P rotein P ilot's ability to simultaneously predict multiple modifications showed an advantage from P roteo M iner treatment for modified peptide identification. We demonstrate that complementary approaches in the analysis pipeline provide comprehensive results for the whole saliva data set acquired on an LTQ O rbitrap. Overall our results establish a workflow for improved protein identification from high mass accuracy data.