Dataset Information

Quantitative Proteomics Benchmark Dataset to evaluate label-free quantitative methods- LC/Orbitrap Fusion MS analysis of E coli proteomes spiked-in Human proteins at 5 different levels (N=20)

ABSTRACT: To unbiasedly evaluate the quantitative performance of different quantitative methods, and compare different popular proteomics data processing workflows, we prepared a benchmark dataset where the various levels of spikeed-in E. Coli proteome that true fold change (i.e. 1 fold, 1.5 fold, 2 fold, 2.5 fold and 3 fold) and true identities of positives/negatives (i.e. E.Coli proteins are true positives while Human proteins are true negatives) are known. To best mimic the proteomics application in comparison of multiple replicates, each fold change group contains 4 replicates, so there are 20 LC-MS/MS analysis in this benchmark dataset. To our knowledge, this spike-in benchmark dataset is largest-scale ever that encompasses 5 different spike level, >500 true positive proteins, and >3000 true negative proteins (2peptide criteria, 1% protein FDR), with a wide concentration dynamic range. The dataset is ideal to test quantitative accuracy, precision, false-positive biomarker discovery and missing data level.

INSTRUMENT(S): Orbitrap Fusion

ORGANISM(S): Homo Sapiens (human) Escherichia Coli

TISSUE(S): Permanent Cell Line Cell

SUBMITTER: XIAOMENG SHEN

LAB HEAD: Jun Qu

PROVIDER: PXD003881 | Pride | 2018-05-16

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	B03_02_150304_human_ecoli_B_3ul_3um_column_95_HCD_OT_2hrs_30B_9B.raw	Raw
	B03_02_150304_human_ecoli_B_3ul_3um_column_95_HCD_OT_2hrs_30B_9B.raw.mzXML	Mzxml
	B03_02_150304_human_ecoli_B_3ul_3um_column_95_HCD_OT_2hrs_30B_9B.raw.mzid.gz	Mzid
	B03_02_150304_human_ecoli_B_3ul_3um_column_95_HCD_OT_2hrs_30B_9B.raw.pride.mgf.gz	Mgf
	B03_02_150304_human_ecoli_B_3ul_3um_column_95_HCD_OT_2hrs_30B_9B.raw.pride.mztab.gz	Mztab

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Publications

IonStar enables high-precision, low-missing-data proteomics quantification in large biological cohorts.

Shen Xiaomeng X Shen Shichen S Li Jun J Hu Qiang Q Nie Lei L Tu Chengjian C Wang Xue X Poulsen David J DJ Orsburn Benjamin C BC Wang Jianmin J Qu Jun J

Proceedings of the National Academy of Sciences of the United States of America 20180509 21

Reproducible quantification of large biological cohorts is critical for clinical/pharmaceutical proteomics yet remains challenging because most prevalent methods suffer from drastically declined commonly quantified proteins and substantially deteriorated quantitative quality as cohort size expands. MS2-based data-independent acquisition approaches represent tremendous advancements in reproducible protein measurement, but often with limited depth. We developed IonStar, an MS1-based quantitative a ...[more]

PMID: 29743190

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