A comparative evaluation of software for the analysis of liquid chromatography-tandem mass spectrometry data from isotope coded affinity tag experimentsShow others and affiliations
2005 (English)In: Proteomics, ISSN 1615-9853, E-ISSN 1615-9861, Vol. 5, no 11, p. 2748-2760Article in journal (Refereed) Published
Abstract [en]
The options available for processing quantitative data from isotope coded affinity tag (ICAT) experiments have mostly been confined to software specific to the instrument of acquisition. However, recent developments with data format conversion have subsequently increased such processing opportunities. In the present study, data sets from ICAT experiments, analysed with liquid chromatography/tandem mass spectrometry (MS/MS), using an Applied Biosystems QSTAR Pulsar quadrupole-TOF mass spectrometer, were processed in triplicate using separate mass spectrometry software packages. The programs Pro ICAT, Spectrum Mill and SEQUEST with XPRESS were employed. Attention was paid towards the extent of common identification and agreement of quantitative results, with additional interest in the flexibility and productivity of these programs. The comparisons were made with data from the analysis of a specifically prepared test mixture, nine proteins at a range of relative concentration ratios from 0.1 to 10 (light to heavy labelled forms), as a known control, and data selected from an ICAT study involving the measurement of cytokine induced protein expression in human lymphoblasts, as an applied example. Dissimilarities were detected in peptide identification that reflected how the associated scoring parameters favoured information from the MS/MS data sets. Accordingly, there were differences in the numbers of peptides and protein identifications, although from these it was apparent that both confirmatory and complementary information was present. In the quantitative results from the three programs, no statistically significant differences were observed.
Place, publisher, year, edition, pages
Wiley-VCH Verlagsgesellschaft, 2005. Vol. 5, no 11, p. 2748-2760
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:oru:diva-70894DOI: 10.1002/pmic.200401187ISI: 000231036100005PubMedID: 15952233Scopus ID: 2-s2.0-23044512070OAI: oai:DiVA.org:oru-70894DiVA, id: diva2:1345895
2019-08-262019-08-262019-08-28Bibliographically approved