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MS Amanda, a universal identification algorithm optimized for high accuracy tandem mass spectra.

Dorfer V, Pichler P, Stranzl T, Stadlmann J, Taus T, Winkler S, Mechtler K - J. Proteome Res. (2014)

Bottom Line: Today's highly accurate spectra provided by modern tandem mass spectrometers offer considerable advantages for the analysis of proteomic samples of increased complexity.While most widely used search engines were developed when high-resolution mass spectrometry data were not readily available for fragment ion masses, we have designed a scoring algorithm particularly suitable for high mass accuracy.The algorithm confidently explains more spectra at the same false discovery rate than Mascot or SEQUEST on examined high mass accuracy data sets, with excellent overlap and identical peptide sequence identification for most spectra also explained by Mascot or SEQUEST.

View Article: PubMed Central - PubMed

Affiliation: Bioinformatics Research Group, University of Applied Sciences Upper Austria , Softwarepark 11, 4232 Hagenberg, Austria.

ABSTRACT
Today's highly accurate spectra provided by modern tandem mass spectrometers offer considerable advantages for the analysis of proteomic samples of increased complexity. Among other factors, the quantity of reliably identified peptides is considerably influenced by the peptide identification algorithm. While most widely used search engines were developed when high-resolution mass spectrometry data were not readily available for fragment ion masses, we have designed a scoring algorithm particularly suitable for high mass accuracy. Our algorithm, MS Amanda, is generally applicable to HCD, ETD, and CID fragmentation type data. The algorithm confidently explains more spectra at the same false discovery rate than Mascot or SEQUEST on examined high mass accuracy data sets, with excellent overlap and identical peptide sequence identification for most spectra also explained by Mascot or SEQUEST. MS Amanda, available at http://ms.imp.ac.at/?goto=msamanda , is provided free of charge both as standalone version for integration into custom workflows and as a plugin for the Proteome Discoverer platform.

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Related in: MedlinePlus

Overlap of target PSMs based on one HCD HeLa replicate.MS Amandaexplains large fractions of PSMs also identified by Mascot and SEQUEST.Further, our algorithm explains many peptides otherwise uniquely identifiedby either Mascot or SEQUEST.
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fig4: Overlap of target PSMs based on one HCD HeLa replicate.MS Amandaexplains large fractions of PSMs also identified by Mascot and SEQUEST.Further, our algorithm explains many peptides otherwise uniquely identifiedby either Mascot or SEQUEST.

Mentions: Toshow the validity of our approach, weinvestigated the overlap in target PSM identification for all threesearch algorithms. Analyzing one replicate of the HCD HeLa data set(MS Amanda 15 091 PSMs, Mascot 12 386 PSMs, SEQUEST12 858 PSMs), 9921 spectra were commonly identified by allthree search engines (Figure 4). While MS Amandaidentified considerably more unique PSMs than compared search engines,the capability of MS Amanda to identify large fractions of peptidesfound by either Mascot or SEQUEST is noteworthy; 92% of the PSMs identifiedby Mascot and further 92% of those identified by SEQUEST are reliablyfound by MS Amanda, while only 80% of PSMs identified by SEQUEST and83% of PSMs identified by Mascot are also found by the respectiveother search engine. This highlights that MS Amanda is remarkablycapable of explaining spectra otherwise uniquely identified by eitherMascot or SEQUEST.


MS Amanda, a universal identification algorithm optimized for high accuracy tandem mass spectra.

Dorfer V, Pichler P, Stranzl T, Stadlmann J, Taus T, Winkler S, Mechtler K - J. Proteome Res. (2014)

Overlap of target PSMs based on one HCD HeLa replicate.MS Amandaexplains large fractions of PSMs also identified by Mascot and SEQUEST.Further, our algorithm explains many peptides otherwise uniquely identifiedby either Mascot or SEQUEST.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4119474&req=5

fig4: Overlap of target PSMs based on one HCD HeLa replicate.MS Amandaexplains large fractions of PSMs also identified by Mascot and SEQUEST.Further, our algorithm explains many peptides otherwise uniquely identifiedby either Mascot or SEQUEST.
Mentions: Toshow the validity of our approach, weinvestigated the overlap in target PSM identification for all threesearch algorithms. Analyzing one replicate of the HCD HeLa data set(MS Amanda 15 091 PSMs, Mascot 12 386 PSMs, SEQUEST12 858 PSMs), 9921 spectra were commonly identified by allthree search engines (Figure 4). While MS Amandaidentified considerably more unique PSMs than compared search engines,the capability of MS Amanda to identify large fractions of peptidesfound by either Mascot or SEQUEST is noteworthy; 92% of the PSMs identifiedby Mascot and further 92% of those identified by SEQUEST are reliablyfound by MS Amanda, while only 80% of PSMs identified by SEQUEST and83% of PSMs identified by Mascot are also found by the respectiveother search engine. This highlights that MS Amanda is remarkablycapable of explaining spectra otherwise uniquely identified by eitherMascot or SEQUEST.

Bottom Line: Today's highly accurate spectra provided by modern tandem mass spectrometers offer considerable advantages for the analysis of proteomic samples of increased complexity.While most widely used search engines were developed when high-resolution mass spectrometry data were not readily available for fragment ion masses, we have designed a scoring algorithm particularly suitable for high mass accuracy.The algorithm confidently explains more spectra at the same false discovery rate than Mascot or SEQUEST on examined high mass accuracy data sets, with excellent overlap and identical peptide sequence identification for most spectra also explained by Mascot or SEQUEST.

View Article: PubMed Central - PubMed

Affiliation: Bioinformatics Research Group, University of Applied Sciences Upper Austria , Softwarepark 11, 4232 Hagenberg, Austria.

ABSTRACT
Today's highly accurate spectra provided by modern tandem mass spectrometers offer considerable advantages for the analysis of proteomic samples of increased complexity. Among other factors, the quantity of reliably identified peptides is considerably influenced by the peptide identification algorithm. While most widely used search engines were developed when high-resolution mass spectrometry data were not readily available for fragment ion masses, we have designed a scoring algorithm particularly suitable for high mass accuracy. Our algorithm, MS Amanda, is generally applicable to HCD, ETD, and CID fragmentation type data. The algorithm confidently explains more spectra at the same false discovery rate than Mascot or SEQUEST on examined high mass accuracy data sets, with excellent overlap and identical peptide sequence identification for most spectra also explained by Mascot or SEQUEST. MS Amanda, available at http://ms.imp.ac.at/?goto=msamanda , is provided free of charge both as standalone version for integration into custom workflows and as a plugin for the Proteome Discoverer platform.

Show MeSH
Related in: MedlinePlus