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Target-small decoy search strategy for false discovery rate estimation.

Hyunwoo Kim1, Sangjeong Lee2, Heejin Park3

  • 1Research Data Sharing Center, Korea Institute of Science and Technology Information, Daejeon, 34141, Republic of Korea.

BMC Bioinformatics
|August 25, 2019
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Summary

A new target-small decoy search strategy significantly reduces computational resources for peptide identification. This method maintains high accuracy comparable to the traditional target-decoy search strategy (TDS), offering a more efficient approach.

Keywords:
False discovery rateTarget-decoy searchTarget-small decoy search

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Area of Science:

  • Proteomics
  • Bioinformatics
  • Computational Biology

Background:

  • Accurate peptide identification relies on estimating the false discovery rate (FDR).
  • The standard target-decoy search strategy (TDS) is effective but computationally intensive due to doubled database size.
  • Increasing protein database sizes exacerbate the inefficiency of TDS.

Purpose of the Study:

  • To introduce a novel target-small decoy search strategy.
  • To verify the reduced database size and search time of the new method.
  • To confirm that the new method retains the accuracy of the traditional TDS.

Main Methods:

  • Implementation of a target-small decoy search strategy.
  • Rigorous verification of the method's performance against TDS.
  • Comparative analysis of search time and database size efficiency.

Main Results:

  • Peptide spectrum matches (PSMs) at 1% FDR showed ~99% overlap between the new method and TDS.
  • The proposed method significantly improves time and space efficiency.
  • Search time was reduced to 1/4 of TDS when using UniProt with a 1/8 decoy database.

Conclusions:

  • The target-small decoy search strategy is nearly as accurate as TDS.
  • The new method offers substantial time and space efficiency improvements over TDS.
  • This approach is particularly beneficial for large-scale proteogenomics databases.