A statistical method for assessing peptide identification confidence in accurate mass and time tag proteomics

Jeffrey R. Stanley; Joshua N. Adkins; Gordon W. Slysz; Matthew E. Monroe; Samuel O. Purvine; Yuliya V. Karpievitch; Gordon A. Anderson; Richard D. Smith; Alan R. Dabney

doi:10.1021/ac2009806

A statistical method for assessing peptide identification confidence in accurate mass and time tag proteomics

Jeffrey R. Stanley, Joshua N. Adkins, Gordon W. Slysz, Matthew E. Monroe, Samuel O. Purvine, Yuliya V. Karpievitch, Gordon A. Anderson, Richard D. Smith, Alan R. Dabney

Research output: Contribution to journal › Article › peer-review

41 Citations (Scopus)

Abstract

Figure Presented Current algorithms for quantifying peptide identification confidence in the accurate mass and time (AMT) tag approach assume that the AMT tags themselves have been correctly identified. However, there is uncertainty in the identification of AMT tags, because this is based on matching LC-MS/MS fragmentation spectra to peptide sequences. In this paper, we incorporate confidence measures for the AMT tag identifications into the calculation of probabilities for correct matches to an AMT tag database, resulting in a more accurate overall measure of identification confidence for the AMT tag approach. The method is referenced as Statistical Tools for AMT Tag Confidence (STAC). STAC additionally provides a uniqueness probability (UP) to help distinguish between multiple matches to an AMT tag and a method to calculate an overall false discovery rate (FDR). STAC is freely available for download, as both a command line and a Windows graphical application.

Original language	English
Pages (from-to)	6135-6140
Number of pages	6
Journal	Analytical Chemistry
Volume	83
Issue number	16
DOIs	https://doi.org/10.1021/ac2009806
Publication status	Published - 15 Aug 2011
Externally published	Yes

Access to Document

10.1021/ac2009806

Cite this

@article{fc6914797420469eaf903baae1f9c847,

title = "A statistical method for assessing peptide identification confidence in accurate mass and time tag proteomics",

abstract = "Figure Presented Current algorithms for quantifying peptide identification confidence in the accurate mass and time (AMT) tag approach assume that the AMT tags themselves have been correctly identified. However, there is uncertainty in the identification of AMT tags, because this is based on matching LC-MS/MS fragmentation spectra to peptide sequences. In this paper, we incorporate confidence measures for the AMT tag identifications into the calculation of probabilities for correct matches to an AMT tag database, resulting in a more accurate overall measure of identification confidence for the AMT tag approach. The method is referenced as Statistical Tools for AMT Tag Confidence (STAC). STAC additionally provides a uniqueness probability (UP) to help distinguish between multiple matches to an AMT tag and a method to calculate an overall false discovery rate (FDR). STAC is freely available for download, as both a command line and a Windows graphical application.",

author = "Stanley, {Jeffrey R.} and Adkins, {Joshua N.} and Slysz, {Gordon W.} and Monroe, {Matthew E.} and Purvine, {Samuel O.} and Karpievitch, {Yuliya V.} and Anderson, {Gordon A.} and Smith, {Richard D.} and Dabney, {Alan R.}",

year = "2011",

month = aug,

day = "15",

doi = "10.1021/ac2009806",

language = "English",

volume = "83",

pages = "6135--6140",

journal = "Analytical Chemistry",

issn = "0003-2700",

publisher = "American Chemical Society",

number = "16",

}

TY - JOUR

T1 - A statistical method for assessing peptide identification confidence in accurate mass and time tag proteomics

AU - Stanley, Jeffrey R.

AU - Adkins, Joshua N.

AU - Slysz, Gordon W.

AU - Monroe, Matthew E.

AU - Purvine, Samuel O.

AU - Karpievitch, Yuliya V.

AU - Anderson, Gordon A.

AU - Smith, Richard D.

AU - Dabney, Alan R.

PY - 2011/8/15

Y1 - 2011/8/15

N2 - Figure Presented Current algorithms for quantifying peptide identification confidence in the accurate mass and time (AMT) tag approach assume that the AMT tags themselves have been correctly identified. However, there is uncertainty in the identification of AMT tags, because this is based on matching LC-MS/MS fragmentation spectra to peptide sequences. In this paper, we incorporate confidence measures for the AMT tag identifications into the calculation of probabilities for correct matches to an AMT tag database, resulting in a more accurate overall measure of identification confidence for the AMT tag approach. The method is referenced as Statistical Tools for AMT Tag Confidence (STAC). STAC additionally provides a uniqueness probability (UP) to help distinguish between multiple matches to an AMT tag and a method to calculate an overall false discovery rate (FDR). STAC is freely available for download, as both a command line and a Windows graphical application.

AB - Figure Presented Current algorithms for quantifying peptide identification confidence in the accurate mass and time (AMT) tag approach assume that the AMT tags themselves have been correctly identified. However, there is uncertainty in the identification of AMT tags, because this is based on matching LC-MS/MS fragmentation spectra to peptide sequences. In this paper, we incorporate confidence measures for the AMT tag identifications into the calculation of probabilities for correct matches to an AMT tag database, resulting in a more accurate overall measure of identification confidence for the AMT tag approach. The method is referenced as Statistical Tools for AMT Tag Confidence (STAC). STAC additionally provides a uniqueness probability (UP) to help distinguish between multiple matches to an AMT tag and a method to calculate an overall false discovery rate (FDR). STAC is freely available for download, as both a command line and a Windows graphical application.

UR - http://www.scopus.com/inward/record.url?scp=80051746323&partnerID=8YFLogxK

U2 - 10.1021/ac2009806

DO - 10.1021/ac2009806

M3 - Article

C2 - 21692516

AN - SCOPUS:80051746323

SN - 0003-2700

VL - 83

SP - 6135

EP - 6140

JO - Analytical Chemistry

JF - Analytical Chemistry

IS - 16

ER -

A statistical method for assessing peptide identification confidence in accurate mass and time tag proteomics

Abstract

Access to Document

Other files and links

Fingerprint

Cite this