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Latin Squares Spike-in Dataset for Comparisons of Statistical Methods

ABSTRACT: 21 proteins of three different size catgeories were purchased from a commercial supplier and used in different runs at different volumes. A yeast proteome background was present in every sample. This allows researchers to download the raw data, develop their own mathematical methods, and compare to others' methods when they upload their processed data to a Shiny application that calculates a range of performance measures. In the present study, different methods of summarising peptides to proteins and normalising between channels and between runs were compared.

INSTRUMENT(S): QSTAR

ORGANISM(S): Homo Sapiens (human) Bos Taurus (bovine) Bacillus Licheniformis Schistosoma Japonicum (blood Fluke) Saccharomyces Cerevisiae (baker's Yeast)

SUBMITTER: Dario Strbenac

LAB HEAD: Professor Susan Wilson

PROVIDER: PXD003608 | Pride | 2017-06-12

REPOSITORIES: Pride

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Dataset's files

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			Action	DRS
	R1-1.wiff	Wiff
	R1-1.wiff.scan	Wiff
	R1-2.wiff	Wiff
	R1-2.wiff.scan	Wiff
	R1-3.wiff	Wiff

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Publications

Quantitative Performance Evaluator for Proteomics (QPEP): Web-based Application for Reproducible Evaluation of Proteomics Preprocessing Methods.

Strbenac Dario D Zhong Ling L Raftery Mark J MJ Wang Penghao P Wilson Susan R SR Armstrong Nicola J NJ Yang Jean Y H JYH

Journal of proteome research 20170605 7

Tandem mass spectrometry is one of the most popular techniques for quantitation of proteomes. There exists a large variety of options in each stage of data preprocessing that impact the bias and variance of the summarized protein-level values. Using a newly released data set satisfying a replicated Latin squares design, a diverse set of performance metrics has been developed and implemented in a web-based application, Quantitative Performance Evaluator for Proteomics (QPEP). QPEP has the flexibi ...[more]

PMID: 28580786

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