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We calculated the proportion of true and false proteins that each domain was associated, e.g., the tropomyosin domain was found in 20 TRUE proteins and 42 FALSE protein, so the proportions are 20/62 = 0.32 and 42/62 = 0.68 for TRUE and FALSE respectively.
Since shotgun proteomics is a peptide-based approach, the false protein identifications can occur as a result of incorrect assignment of fragmented ion spectra to peptide sequence as well as further inferring of protein identifications.
Proteins identified below a 1% false protein discovery rate were considered significant.
To increase confidence in protein identification, the dataset (1% false protein discovery rate) was filtered by a protein group probability of 0.95 using the ProteinProphet algorithm [73].
Since the tissue surrogates consisted of a defined set of proteins, it was possible to calculate the average false protein identification rate (number of non bovine, equine or Gallus proteins identified by MS/MS) for each sample, as shown in Table 3.
The Uniprot database has many duplicate entries that may result in false protein homolog associations when using NanoUPLC-MSE analysis.
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Furthermore, as recommended by CPAT, 0.38 is the optimum cutoff to filter false protein-coding genes in fishes (Wang et al. 2013).
This is achieved by parameterizing two Gaussian densities with the means and variances of SVM scores for True proteins, and False proteins.
All the RF data we show on chromosomal (true) and nonchromosomal (false) proteins, except in Figure 3 A, are derived from these cross-validation data.
We next applied a cross-validation procedure based on a high-quality protein-protein interactions dataset (see Additional file 3) to control the potential effect of false positive protein-protein interactions [ 13].
To identify false positive proteins, proteins derived from each organism and complete culture medium were analyzed with C. albicans, M. musculus database for macrophage, and Bos taurus database for complete culture medium from NCBI (http://www.ncbi.nlm.nih.gov/genome?term=bos%20taurus).
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