About Multi-Q 2
We present Multi-Q 2, a software tool with graphical interfaces for isobaric-labeling quantitation which is capable of generating the highest quantitation accuracy and the largest quantitation coverage compared to state-of-the-art tools.
Isobaric-labeling experiments have become popular for quantitative proteomics because of its multiplexed capability, allowing for quantifying thousands of proteins from multiple samples in a single run. Two major objectives of bioinformatics analysis of isobaric labeling experiments are enlarging quantitation coverage (i.e., the number of quantified proteins) and improving quantitation accuracy. As for the former, Multi-Q 2 supports identification results from Trans-Proteomic Pipeline (TPP), PeptideShaker, and the commercial Proteome Discoverer, offering up to 10% to 12% improvement in coverage compared with MaxQuant and PatternLab. As for the latter, Multi-Q 2 is equipped with various algorithms in different steps of a quantitation pipeline, yielding more than three hundred algorithmic combinations. With proper selection of quantitation algorithms, Multi-Q 2 can achieve considerable improvement in quantitation accuracy over existing software tools. For example, the average error rate (AER) of Multi-Q 2 for four standard proteins in a TMT-6 data set of Erwinia carotovora lysate is 0.121, compared favorably over MaxQuant, PatternLab, and Libra, which produce AER from 0.167 to 0.286. For another standard data set of human A549 cell lysate, Multi-Q 2 outperforms three other tools in terms of area under the curve of coverage v.s. deviation, AER, and root mean square error. We also demonstrate that different algorithmic combinations have different strengths and are suitable in different scenarios. Thus, the flexibility of customizing quantitation algorithms offered by Multi-Q 2 can be useful for biomarker discovery.
Multi-Q 2 provides interactive graphical user interfaces to display protein, peptide, PSM ratios as well as raw and processed reporter ion intensities. Moreover, a heatmap module is implemented to cluster proteins based on the calculated ratios using hierarchical clustering, K-means, and fuzzy C-means, facilitating users to perform further investigations. Multi-Q 2 software, user manual, and all the necessary files for quantifying four sample data sets are available for download at http://ms.iis.sinica.edu.tw/COmics/Software_Multi-Q2.html. We believe the tool can benefit the proteomics community to more efficiently and effectively discover differentially expressed proteins with isobaric-labeling experiments.
Chen et al., "Multi-Q 2: a versatile isobaric labeling quantitation tool for improved quantification accuracy and coverage"
(Manuscript submitted), 2020.