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Charge State Estimation for Tandem MassSpectrometry Proteomics
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High-throughput protein analysis by tandem mass spectrometry produces anywhere from
thousands to millions of spectra that are being used for peptide and protein identifications.
Though each spectrum corresponds only to one charged peptide (ion) state, repetitive database
searches of multiple charge states are typically conducted since the resolution of many
common mass spectrometers is not sufficient to determine the charge state. The resulting
database searches are both error-prone and time-consuming. We describe a straightforward,
accurate approach on charge state estimation (CHASTE). CHASTE relies on fragment ion
peak distributions, and by using reliable logistic regression models, combines different measurements
to improve its accuracy. CHASTE's performance has been validated on data sets,
comprised of known peptide dissociation spectra, obtained by replicate analyses of our earlier
developed protein standard mixture using ion trap mass spectrometers at different laboratories.
CHASTE was able to reduce number of needed database searches by at least 60%
and the number of redundant searches by at least 90% virtually without any informational
loss. This greatly alleviates one of the major bottlenecks in high throughput peptide and protein
identifications. Thresholds and parameter estimates can be tailored to specific analysis
situations, pipelines, and instrumentations. CHASTE was implemented in Java GUI-based
and command-line-based interfaces.
Title: Charge State Estimation for Tandem MassSpectrometry Proteomics
Description:
High-throughput protein analysis by tandem mass spectrometry produces anywhere from
thousands to millions of spectra that are being used for peptide and protein identifications.
Though each spectrum corresponds only to one charged peptide (ion) state, repetitive database
searches of multiple charge states are typically conducted since the resolution of many
common mass spectrometers is not sufficient to determine the charge state.
The resulting
database searches are both error-prone and time-consuming.
We describe a straightforward,
accurate approach on charge state estimation (CHASTE).
CHASTE relies on fragment ion
peak distributions, and by using reliable logistic regression models, combines different measurements
to improve its accuracy.
CHASTE's performance has been validated on data sets,
comprised of known peptide dissociation spectra, obtained by replicate analyses of our earlier
developed protein standard mixture using ion trap mass spectrometers at different laboratories.
CHASTE was able to reduce number of needed database searches by at least 60%
and the number of redundant searches by at least 90% virtually without any informational
loss.
This greatly alleviates one of the major bottlenecks in high throughput peptide and protein
identifications.
Thresholds and parameter estimates can be tailored to specific analysis
situations, pipelines, and instrumentations.
CHASTE was implemented in Java GUI-based
and command-line-based interfaces.
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