Target-small decoy search strategy for false discovery rate estimation
Autor: | Sangjeong Lee, Heejin Park, Hyunwoo Kim |
---|---|
Rok vydání: | 2019 |
Předmět: |
False discovery rate
Computer science Peptide lcsh:Computer applications to medicine. Medical informatics computer.software_genre Biochemistry Cell Line Target-decoy search 03 medical and health sciences 0302 clinical medicine Structural Biology Humans Databases Protein lcsh:QH301-705.5 Molecular Biology 030304 developmental biology chemistry.chemical_classification 0303 health sciences Methodology Article Applied Mathematics Computational Biology Protein database Proteogenomics Computer Science Applications Identification (information) lcsh:Biology (General) chemistry Target-small decoy search 030220 oncology & carcinogenesis lcsh:R858-859.7 Data mining UniProt DNA microarray Peptides Decoy computer Algorithms |
Zdroj: | BMC Bioinformatics BMC Bioinformatics, Vol 20, Iss 1, Pp 1-6 (2019) |
ISSN: | 1471-2105 |
Popis: | Background One of the most important steps in peptide identification is to estimate the false discovery rate (FDR). The most commonly used method for estimating FDR is the target-decoy search strategy (TDS). While this method is simple and effective, it is time/space-inefficient because it searches a database that is twice as large as the original protein database. This inefficiency problem becomes more evident as protein databases get bigger and bigger. We propose a target-small decoy search strategy and present a rigorous verification that it reduces the database size and search time while retaining the accuracy of target-decoy search strategy (TDS). Results We show that peptide spectrum matches (PSMs) obtained at 1% FDR in TDS overlap ~ 99% with those in our method. (Considering that 1% FDR is used, 99% overlap means our method is very accurate.) Moreover, our method is more time/space-efficient than TDS. The search time of our method is reduced to only 1/4 of that of TDS when UniProt and its 1/8 decoy database are used. Conclusions We demonstrate that our method is almost as accurate as TDS and more time/space-efficient than TDS. Since the efficiency of our method is more evident as the database size increases, our method is expected to be useful for identifying peptides in proteogenomics databases constructed from inflated databases using genomic data. Electronic supplementary material The online version of this article (10.1186/s12859-019-3034-8) contains supplementary material, which is available to authorized users. |
Databáze: | OpenAIRE |
Externí odkaz: |