Introduction to the ABRF iPRG2008 Study

A significant challenge in proteome informatics is accurate and concise reporting of protein identification data that result from mass spectrometry-based proteomic workflows. The Paris Guidelines represent the proteomics communityกฏs efforts to devise a standard methodology for reporting protein identification data.

Given these guidelines, the Proteome Informatics Research Group (iPRG) of the Association of Biomolecular Resource Facilities (ABRF) proposes to assess the consistency of protein identification analysis. The iPRG2008 study focuses on evaluating the ability of proteomics laboratories to determine the identities of a complex mixture of proteins present in a single mass spectral dataset.

The primary goals of this study are to provide each participating laboratory an opportunity to evaluate its capabilities and approaches with regard to:
· Bioinformatics tools used to make and consolidate protein identifications derived from a common data set and a common reference database.
· Report those identifications using common reporting criteria.

The data set for this study consists of mouse samples that were digested with trypsin, resolved into 13 fractions by strong cation exchange chromatography, and then analyzed by LC-MS/MS (3200 QTRAP). Most of the fractions were analyzed with successive rounds of exclusion in order to identify more peptides in each fraction. This resulted in the total of 29 acquisition sets and 41,977 spectra.

The determination of the "correct" proteins is performed by voting strategy. Each iPRG expert analyzes the data independently with the tools of their choosing like any study respondent. The resulted protein identifications are evaluated and graded into several categories with different confidence. This pool of protein identifications serves as a benchmark to evaluate the performance of the identification results each participant submitted.

In January 2008, we participated this study with pFind (a database-searching software for protein identification via tandem mass spectrometry) and pCompare (an in-house software tool for peptide identification result parsing and protein inferring) developed by ourselves. The performance of our results is shown in the following figures extracted from an ABRF poster. Now we are taking our efforts to make pFind more reliable and applicable.

Figure 1. Overview of all submissions. Each histogram bin represents an iPRG expert (6 bins on the left) or a participant. The area of histogram bins in green, red, and gray represent the number of correct, false, and uncertain identifications, respectively. This analysis shows that the performance of our software (labeled with 86010) is comparative to that of the experts on an average.


Figure 2. ROC analysis of all submissions. The most ideal performance should be at the utmostly top-left corner of the coordinate chart. The dot within the red square represents our submitted results.

Details about the ABRF iPRG2008 Study, can be found here.