MassUntangler: a novel alignment tool for label-free liquid chromatography-mass spectrometry proteomic data.

摘要: Liquid chromatography-mass spectrometry (LC-MS) has become an important analytical tool for quantitative proteomics and biomarker discovery. In the label-free differential LC-MS approach computational methods are required accurate alignment of peaks extrapolated from experimental raw data accounting retention time m/z signals intensity, which strongly affected by sample matrix instrumental performance. A novel procedure "MassUntangler" pairwise been developed, relying on a pattern-based matching algorithm integrated with filtering algorithms in multi-step approach. The optimized employing two-step Firstly, low-complexity derived enzymatic digestion two standard proteins have analyzed. Then, algorithm's performance evaluated comparing results other achieved using state-of-the-art tools. second step, our used high-complexity consisting peptides obtained Escherichia coli lysate available public repository previously comparison MassUntangler gave excellent terms precision scores (from 80% to 93%) recall 68% 89%), showing performances similar even better than previous developed Considering mass sensitivity accuracy, this allows identification quantification present biological at femtomole level high confidence. procedure's capability aligning corrected distortion studied through hybrid approach, was interfaced OpenMS TOPP MapAligner. aligner yielded results, that integration different bioinformatic approaches should be used.