download0 view559
twitter facebook

공공누리This item is licensed Korea Open Government License

Title
Target-small decoy search strategy for false discovery rate estimation
Author(s)
김현우박희진이상정
Publisher
BioMed Central
Publication Year
2019-08-23
Abstract
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.
Keyword
Target-decoy search; Target-small decoy search; False discovery rate
Journal Title
BMC bioinformatics;
Citation Volume
20
ISSN
1471-2105
DOI
10.1186/s12859-019-3034-8
Files in This Item:
There are no files associated with this item.
Appears in Collections:
7. KISTI 연구성과 > 학술지 발표논문
URI
https://repository.kisti.re.kr/handle/10580/16587
Fulltext
 https://scienceon.kisti.re.kr/srch/selectPORSrchArticle.do?cn=NART108698358
Export
RIS (EndNote)
XLS (Excel)
XML

Browse