PXD006336

PXD006336 is an original dataset announced via ProteomeXchange.

Title	FeatureFinderIdentification (OpenMS) analysis of the iPRG-2015 dataset
Description	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.
HostingRepository	PRIDE
AnnounceDate	2017-07-07
AnnouncementXML	Submission_2017-07-07_05:21:39.xml
DigitalObjectIdentifier	https://dx.doi.org/10.6019/PXD006336
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Supported dataset by repository
PrimarySubmitter	Hendrik Weisser
SpeciesList	scientific name: Saccharomyces cerevisiae (Baker's yeast); NCBI TaxID: 4932;
ModificationList	Deamidated; Oxidation; Acetyl; Carbamidomethyl
Instrument	Q Exactive

Revision	Datetime	Status	ChangeLog Entry
0	2017-04-19 08:08:03	ID requested
⏵ 1	2017-07-07 05:21:40	announced

Weisser H, Choudhary JS, Targeted Feature Detection for Data-Dependent Shotgun Proteomics. J Proteome Res, 16(8):2964-2974(2017) [pubmed]

curator keyword: Technical

submitter keyword: shotgun proteomics, label-free quantification, feature detection, benchmark, iPRG-2015

Jyoti Sharma Choudhary
contact affiliation	Proteomic Mass Spectrometry, Wellcome Trust Sanger Institute, United Kingdom
contact email	jc4@sanger.ac.uk
lab head
Hendrik Weisser
contact affiliation	Wellcome Trust Sanger Institute
contact email	hw5@sanger.ac.uk
dataset submitter

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PRIDE project URI

• PRIDE
  1. PXD006336
     1. Label: PRIDE project
     2. Name: FeatureFinderIdentification (OpenMS) analysis of the iPRG-2015 dataset