.png){kind=icon}
返回
HyperQuant-A Computational Pipeline for Higher Order Multiplexed Quantitative Proteomics
.png){kind=icon}
OA
AI
DOI：10.1021/acsomega.0c00515.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Quantitative proteomics has evolved considerably over the last decade with the advent of higher order multiplexing (HOM) techniques. With the development of methods such as-multitagging, cPILOT, hyperplexing, BONPIex, and MITNCAT, the HOM technique is rapidly taking the center stage in multiplexed quantitative proteomics. These studies combined MS1 and MS2 labels in a single experiment enabling higher sample throughput. While HOM is highly promising, the computational analysis is still a big challenge, as the available tools cannot harness its power completely. We have developed a new quantitative pipeline, HyperQuant to aid in accurately quantitating complex HOM data. The pipeline uses identification results from either MaxQuant or any other search engine and quantitation results from QuantWiz(IQ). The Mapper and Combiner modules of HyperQuant allow facile integration of the labeled data, along with peptide spectrum match (PSM) intensity/ ratio integration for proteins, respectively, for each PSM label combination. This also includes appropriate combination of replicates/fractions before summarizing the protein intensity/ratio, leading to robust quantitation. To the best of our knowledge, this is the first tool for the quantitation of HOM data with flexibility for any combination of MS(1 )and MS2 labels. We demonstrate its utility in analyzing two 18-plex data sets from the hyperplexing and the BONplex studies. The tool is open source and freely available for noncommercial use. HyperQuant is a highly valuable tool that will help in advancing the field of multiplexed quantitative proteomics.
Keyword:
TANDEM MASS TAGS
MYCOBACTERIUM-TUBERCULOSIS
TEMPORAL DYNAMICS
IMMUNE-RESPONSE
CELL-CULTURE
RECEPTOR
QUANTIFICATION
SPECTROMETRY
SECRETOME
PEPTIDE
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4.3
论文数:
3.4W
被引数:
9.8W
机构
引用论文
Social network architecture of human immune cells unveiled by quantitative proteomics.png)
NATURE IMMUNOLOGY
NATURE IMMUNOLOGYIF27.6
PREAI
分享收藏IL-34 and M-CSF share the receptor Fms but are not identical in biological activity and signal activationIL-34和m-csf共享受体Fms，但在生物活性和信号激活方面不相同OAAI
OAAI分享收藏GeneCodis3: a non-redundant and modular enrichment analysis tool for functional genomicsGeneCodis3: 功能基因组学的非冗余和模块化富集分析工具NUCLEIC ACIDS RESEARCHOAAI
NUCLEIC ACIDS RESEARCHIF13.1
OAAI分享收藏Method to compare collision-induced dissociation spectra of peptides: Potential for library searching and subtractive analysisANALYTICAL CHEMISTRY
ANALYTICAL CHEMISTRYIF6.7
PREAI
分享收藏Tandem mass tags:: A novel quantification strategy for comparative analysis of complex protein mixtures by MS/MSANALYTICAL CHEMISTRY
ANALYTICAL CHEMISTRYIF6.7
PREAI
分享收藏Monitoring matrix metalloproteinase activity at the epidermal-dermal interface by SILAC-iTRAQ-TAILSPROTEOMICS
PROTEOMICSIF3.9
PREAI
分享收藏
查看更多内容