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Quartet protein reference materials and datasets for multi-platform assessment of label-free proteomics.

Sha Tian | Dongdong Zhan | Ying Yu | Yunzhi Wang | Mingwei Liu | Subei Tan | Yan Li | Lei Song | Zhaoyu Qin | Xianju Li | Yang Liu | Yao Li | Shuhui Ji | Shanshan Wang | Proteomic Massive Analysis and Quality Control Consortium | Yuanting Zheng | Fuchu He | Jun Qin | Chen Ding
Genome biology | 2023

Quantitative proteomics is an indispensable tool in life science research. However, there is a lack of reference materials for evaluating the reproducibility of label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based measurements among different instruments and laboratories.

Pubmed ID: 37674236

Associated grants

None

Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


Addgene (tool)

RRID:SCR_002037

Non-profit plasmid repository dedicated to helping scientists around the world share high-quality plasmids. Facilitates archiving and distributing DNA-based research reagents and associated data to scientists worldwide. Repository contains over 65,000 plasmids, including special collections on CRISPR, fluorescent proteins, and ready-to-use viral preparations. There is no cost for scientists to deposit plasmids, which saves time and money associated with shipping plasmids themselves. All plasmids are fully sequenced for validation and sequencing data is openly available. We handle the appropriate Material Transfer Agreements (MTA) with institutions, facilitating open exchange and offering intellectual property and liability protection for depositing scientists. Furthermore, we curate free educational resources for the scientific community including a blog, eBooks, video protocols, and detailed molecular biology resources.

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Gene Ontology (tool)

RRID:SCR_002811

Computable knowledge regarding functions of genes and gene products. GO resources include biomedical ontologies that cover molecular domains of all life forms as well as extensive compilations of gene product annotations to these ontologies that provide largely species-neutral, comprehensive statements about what gene products do. Used to standardize representation of gene and gene product attributes across species and databases.

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ProteomeXchange (tool)

RRID:SCR_004055

A data repository for proteomic data sets. The ProteomeExchange consortium, as a whole, aims to provide a coordinated submission of MS proteomics data to the main existing proteomics repositories, as well as to encourage optimal data dissemination. ProteomeXchange provides access to a number of public databases, and users can access and submit data sets to the consortium's PRIDE database and PASSEL/PeptideAtlas.

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Millipore (tool)

RRID:SCR_008983

An Antibody supplier

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Mascot (tool)

RRID:SCR_014322

A software package and server used to identify and characterize proteins from primary sequence databases using mass spectrometry data. Mascot integrates peptide mass fingerprinting, sequence querying, and MS/MS ion searching in order to search for proteins in databases like SwissProt, NCBInr, EMBL EST divisions, contaminants, and cRAP. If a license is purchased, users may: search data sets that exceed the 1200 spectrum limit of the free version; set up automated, high throughput work; add and edit proteins and quantification methods; and search a preferred collection of sequence databases. The software package works with instruments from AB Sciex, Agilent, Bruker, Jeol, Shimadzu, Thermo Scientific, and Waters.

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Percolator: Semi-supervised learning for peptide identification from shotgun proteomics datasets (tool)

RRID:SCR_005040

Percolator post-processes the results of a shotgun proteomics database search program, re-ranking peptide-spectrum matches so that the top of the list is enriched for correct matches. Shotgun proteomics uses liquid chromatography-tandem mass spectrometry to identify proteins in complex biological samples. We describe an algorithm, called Percolator, for improving the rate of peptide identifications from a collection of tandem mass spectra. Percolator uses semi-supervised machine learning to discriminate between correct and decoy spectrum identifications, correctly assigning peptides to 17% more spectra from a tryptic dataset and up to 77% more spectra from non-tryptic digests, relative to a fully supervised approach. The yeast-01 data is available in tab delimetered format. The SEQUEST parameter file and target database for the yeast and worm data are also available.

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