IDPicker 2.0: Improved protein assembly with high discrimination peptide identification filtering.
作者： Ze-Qiang Ma , Surendra Dasari , Matthew C. Chambers , Michael D. Litton , Scott M. Sobecki
DOI: 10.1021/PR900360J
关键词: Shotgun proteomics 、 Computational biology 、 Biology 、 Database search engine 、 Peptide 、 Combinatorial chemistry 、 False discovery rate 、 Tandem mass spectrometry 、 Proteomics 、 Peptide mass fingerprinting 、 Peptide spectral library
摘要: Tandem mass spectrometry-based shotgun proteomics has become a widespread technology for analyzing complex protein mixtures. A number of database searching algorithms have been developed to assign peptide sequences tandem spectra. Assembling the identifications proteins, however, is challenging issue because many peptides are shared among multiple proteins. IDPicker an open-source assembly tool that derives minimum list from filtered specified False Discovery Rate. Here, we update increase confident by combining scores produced search tools. By segregating thresholding using both precursor charge state and tryptic termini, retrieves more assembly. The new version robust against false positive especially in searches multispecies databases, requiring additional novel t...
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