scholarly journals Quality Control and Outlier Detection of Targeted Mass Spectrometry Data from Multiplex Protein Panels

2020 ◽  
Vol 19 (6) ◽  
pp. 2278-2293
Author(s):  
Irene van den Broek ◽  
Mitra Mastali ◽  
Kelly Mouapi ◽  
Cory Bystrom ◽  
C. Noel Bairey Merz ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Quality Control ◽  
Outlier Detection ◽  
Mass Spectrometry Data

scholarly journals Recent advances in software tools for more generic and precise intact glycopeptide analysis

2020 ◽  
pp. mcp.R120.002090 ◽  
Author(s):  
Weiqian Cao ◽  
Mingqi Liu ◽  
Siyuan Kong ◽  
Mengxi Wu ◽  
Yang Zhang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Systematic Review ◽  
Quality Control ◽  
Software Tools ◽  
Mass Spectrometry Data ◽  
Identification Process ◽  
Advantages And Disadvantages ◽  
Recent Advances ◽  
Glycopeptide Analysis

Intact glycopeptide identification has long been known as a key and challenging barrier to the comprehensive and accurate understanding the role of glycosylation in an organism. Intact glycopeptide analysis is a blossoming field that has received increasing attention in recent years. Mass spectrometry (MS)-based strategies and relative software tools are major drivers that have greatly facilitated the analysis of intact glycopeptides, particularly intact N-glycopeptides. This manuscript provides a systematic review of the intact glycopeptide identification process using mass spectrometry data generated in shotgun proteomic experiments, which typically focus on N-glycopeptide analysis. Particular attention is paid to the software tools that have been recently developed in the last decade for the interpretation and quality control of glycopeptide spectra acquired using different MS strategies. The review also provides information about the characteristics and applications of these software tools, discusses their advantages and disadvantages, and concludes with a discussion of outstanding tools.

scholarly journals MALDIrppa: quality control and robust analysis for mass spectrometry data

2017 ◽  
Vol 34 (3) ◽  
pp. 522-523 ◽  
Author(s):  
Javier Palarea-Albaladejo ◽  
Kevin Mclean ◽  
Frank Wright ◽  
David G E Smith
Keyword(s):  
Mass Spectrometry ◽  
Quality Control ◽  
Mass Spectrometry Data ◽  
Robust Analysis

scholarly journals OutlierD: an R package for outlier detection using quantile regression on mass spectrometry data

2008 ◽  
Vol 24 (6) ◽  
pp. 882-884 ◽  
Author(s):  
HyungJun Cho ◽  
Yang-jin Kim ◽  
Hee Jung Jung ◽  
Sang-Won Lee ◽  
Jae Won Lee
Keyword(s):  
Mass Spectrometry ◽  
Quantile Regression ◽  
Outlier Detection ◽  
R Package ◽  
Mass Spectrometry Data

154: Integration of TPSA and High-Throughput Mass Spectrometry Data Improves Prostate Cancer Prediction

2007 ◽  
Vol 177 (4S) ◽  
pp. 52-53
Author(s):  
Stefano Ongarello ◽  
Eberhard Steiner ◽  
Regina Achleitner ◽  
Isabel Feuerstein ◽  
Birgit Stenzel ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Mass Spectrometry ◽  
High Throughput ◽  
Mass Spectrometry Data ◽  
Cancer Prediction

Unrestrictive protein modification localization and quality control for open search of mass spectra

2018 ◽  
Author(s):  
Zhiwu An ◽  
Fuzhou Gong ◽  
Yan Fu
Keyword(s):  
Mass Spectrometry ◽  
Quality Control ◽  
Tandem Mass Spectrometry ◽  
Mass Spectra ◽  
Protein Modification ◽  
Software Tool ◽  
Tandem Mass ◽  
Simulation Data ◽  
Post Translational Modifications

We have developed PTMiner, a first software tool for automated, confident filtering, localization and annotation of protein post-translational modifications identified by open (mass-tolerant) search of large tandem mass spectrometry datasets. The performance of the software was validated on carefully designed simulation data. <br>

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