Merged data set 1 In a previous analysis we merged the data from both of these

Merged data set 1 in a previous analysis we merged

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Merged data set-1: In a previous analysis, we merged the data from both of these 2DE datasets, comparing this new larger protein abundance set with a comprehensive mRNA expression data set. This mRNA expression reference set was constructed through iteratively combining, in a non-trivial fashion, three Affymetrix sets and a SAGE dataset [27]. Using these new reference data sets, we were able to do an all-against-all comparison of mRNA and protein expression levels in addition to a number of analyses comparing protein and mRNA expression using smaller, but broad categories [27,28]. Given the difficult, laborious, and limiting nature of 2DE analysis, much of the newer protein abundance determinations have been done using the MudPit and derivative technologies. One caveat: Mudpit data on its own, is semi-quantitative in that the number of peptides determined is relative to the actual protein abundance within the cell[29]. 5
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MudPit-1: Washburn et al[29] used MUDPIT to analyze and detect 1484 arbitrary proteins- i.e. they were able to detect a somewhat random sampling of proteins independent of their abundance, localization, size or hydrophobicity. In a further experiment the authors, comparing expression ratios for both proteins and mRNA levels, found that although they could not find correlations for individual loci, they could find overall correlations when looking at pathways and complexes of proteins that functioned together [19]. MudPit-2: Peng et al [30] analyzed 1504 yeast proteins with a false positive rate -misidentification of a protein- of less than 1%. In their analysis they contrasted their methodology with that of Washburn et al with which there was significant overlap. New Merged Dataset: Merged data set-2 Expanding upon our previous merged data set, we constructed a new merged data set using the two 2DE and two Mudpit data sets presented above. Succinctly (more information is available on our web site: - protein/), we transformed each of the protein abundance data sets into more quantitative data via fitting them individually onto the reference mRNA expression data set. The Mudpit-1 dataset was also fit onto the more finely-grained Mudpit-2 dataset. Each of the new, fitted datasets was then inversely transformed back into protein space. These datasets were then combined into a larger reference data set; when we had more than one abundance value for an ORF, we chose the value from the dataset according to a proscribed quality-ranking (see figure 1 caption). The resulting set contained protein abundance for ~2000 ORFs. (Although some may argue that the less quantitative nature of some of the MudPit data should not be used to compare with the mRNA data, we feel that the merging process creates a more quantitative and representative data set.) Using this data we could compare, globally, mRNA expression and protein abundance (Figure 1a) as well as looking at smaller, broad, categories -i.e.
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