Welcome to MAP


MAP (Model-based Analysis of Proteomic data), is designed to statistically compare the proteomic profiles generated from different biological samples using the isotope labeling based mass spectrometry (MS) technique and directly identify proteins with significant abundance changes. Unlike many existing tools for this purpose, it does not require parallel technical replicates to estimate technical variations, and, instead, uses a novel step-by-step regression analysis to directly model technical variations from the profiles under comparison. Therefore, experimental designs and their expenses can be simplified and reduced for more practices.

Web application now has 2 basic modules:

1. MAP Module

It takes two proteomic profiles generated from different samples as input, in which the MS intensities could be assigned to either protein level or peptide level. It will report a table of statistics, which include the log2-ratio of normalized MS intensities for each protein/peptide and a P-value to describe the significance of its intensity change, together with three figures describing the whole analysis.

2. Integration Module

It is used to compare the proteomic profiling data of two different samples with multiple biological replicates (typically generated in different MS runs). Before running this module, the user first needs to repeatedly perform pairwise cross-sample comparison with the profiles generated in the same MS run using MAP module, and collect the output table of each comparison. Then, Integration module takes these tables as input and finally report the best or the second best P-value among all replicates for each protein. Here, we recommend to use the second best P-value to rank and select the final differentially expressed proteins.

Currently, this work is under review. One of the projects was applied MAP (some of them used the preliminary version of it) has been published.

You may cite the above article before the MAP published.

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