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FeatureFinderIdentification (OpenMS) analysis of the iPRG-2015 dataset

ABSTRACT: Benchmark of FeatureFinderIdentification (FFId), a targeted feature detection algorithm for use in label-free quantification, developed in the OpenMS software framework. The dataset used for the evaluation comes from the iPRG-2015 study ("Differential abundance analysis in label-free quantitative proteomics"), created by the Proteome Informatics Research Group (iPRG) of the Association of Biomolecular Resource Facilities (ABRF); see https://abrf.org/research-group/proteome-informatics-research-group-iprg. The samples contain yeast protein digest spiked with six digested proteins in varying, known concentrations.

INSTRUMENT(S):

ORGANISM(S): Saccharomyces Cerevisiae (baker's Yeast)

TISSUE(S): Cell Culture

SUBMITTER: Hendrik Weisser

LAB HEAD: Jyoti Sharma Choudhary

PROVIDER: PXD006336 | Pride | 2017-07-07

REPOSITORIES: Pride

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Dataset's files

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			Action	DRS
	FFId_internal_1_A.featureXML	Other
	FFId_internal_1_B.featureXML	Other
	FFId_internal_1_C.featureXML	Other
	FFId_internal_2_A.featureXML	Other
	FFId_internal_2_B.featureXML	Other

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Publications

Targeted Feature Detection for Data-Dependent Shotgun Proteomics.

Weisser Hendrik H Choudhary Jyoti S JS

Journal of proteome research 20170719 8

Label-free quantification of shotgun LC-MS/MS data is the prevailing approach in quantitative proteomics but remains computationally nontrivial. The central data analysis step is the detection of peptide-specific signal patterns, called features. Peptide quantification is facilitated by associating signal intensities in features with peptide sequences derived from MS2 spectra; however, missing values due to imperfect feature detection are a common problem. A feature detection approach that direc ...[more]

PMID: 28673088

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