Selected article for: "database search and fragment precursor"

Author: Chernobrovkin, Alexey L.; Zubarev, Roman A.
Title: Detection of Viral Proteins in Human Cells Lines by Xeno-Proteomics: Elimination of the Last Valid Excuse for Not Testing Every Cellular Proteome Dataset for Viral Proteins
  • Document date: 2014_3_11
  • ID: 0hrwqho8_18
    Snippet: To determine the normalized protein abundances, ion current based label-free quantification [32] was used with a minimum of two unique peptides. All raw files were reprocessed with MaxQuant version 1.3.7.4 with Andromeda as a database search engine. MaxQuant analysis included an initial search with a precursor mass tolerance of 20 ppm, the results of which were used for mass recalibration. In the main Andromeda search, precursor mass and fragment.....
    Document: To determine the normalized protein abundances, ion current based label-free quantification [32] was used with a minimum of two unique peptides. All raw files were reprocessed with MaxQuant version 1.3.7.4 with Andromeda as a database search engine. MaxQuant analysis included an initial search with a precursor mass tolerance of 20 ppm, the results of which were used for mass recalibration. In the main Andromeda search, precursor mass and fragment mass had an initial mass tolerance of 6 ppm and 20 ppm, respectively. The search included as variable modifications methionine oxidation and N-terminal acetylation, and carbamidomethyl cysteine as a fixed modification. Minimal peptide length was set to seven amino acids and a maximum of two missed cleavages was allowed. The false discovery rate (FDR) was set to 0.01 for peptide and protein identifications. In the case of several proteins identified with all common peptides, these were combined and reported as one protein group. To verify MaxQuant data, a more precise Quanti program was used designed in house [33] , which yielded similar results.

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