scholarly journals DO-MS: Data-Driven Optimization of Mass Spectrometry Methods

2019 ◽  
Author(s):  
Gray Huffman ◽  
Harrison Specht ◽  
Albert Chen ◽  
Nikolai Slavov
Keyword(s):  
Mass Spectrometry ◽  
Single Cell ◽  
Open Source ◽  
Modular Design ◽  
Analysis Data ◽  
Data Driven ◽  
Ion Transfer ◽  
High Quality ◽  
Elution Peak ◽  
Interactive Data

AbstractThe performance of ultrasensitive LC-MS/MS methods, such as Single-Cell Proteomics by Mass Spectrometry (SCoPE-MS), depends on multiple interdependent parameters. This interdependence makes it challenging to specifically pinpoint bottlenecks in the LC-MS/MS methods and approaches for resolving them. For example, low signal at MS2 level can be due to poor LC separation, ionization, apex targeting, ion transfer, or ion detection. We sought to specifically diagnose such bottlenecks by interactively visualizing data from all levels of bottom-up LC-MS/MS analysis. Many search engines, such as MaxQuant, already provide such data, and we developed an open source platform for their interactive visualization and analysis: Data-driven Optimization of MS (DO-MS). We found that in many cases DO-MS not only specifically diagnosed bottlenecks but also enabled us to rationally optimize them. For example, we used DO-MS to diagnose poor sampling of the elution peak apex and to optimize it, which increased the efficiency of delivering ions for MS2 analysis by 370%. DO-MS is easy to install and use, and its GUI allows for interactive data subsetting and high-quality figure generation. The modular design of DO-MS facilitates customization and expansion. DO-MS is available for download from GitHub: github.com/SlavovLab/DO-MS

What Makes Open Source Software Projects Impactful: A Data-Driven Approach

2020 ◽  
Author(s):  
Huaiwei Yang ◽  
Shuang Liu ◽  
Lin Gui ◽  
Yongxin Zhao ◽  
Jun Sun ◽  
...  
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Data Driven ◽  
Software Projects ◽  
Data Driven Approach

scholarly journals Frontispiz: In Vivo Subcellular Mass Spectrometry Enables Proteo‐Metabolomic Single‐Cell Systems Biology in a Chordate Embryo Developing to a Normally Behaving Tadpole ( X. laevis )

2021 ◽  
Vol 133 (23) ◽  
Author(s):  
Camille Lombard‐Banek ◽  
Jie Li ◽  
Erika P. Portero ◽  
Rosemary M. Onjiko ◽  
Chase D. Singer ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Systems Biology ◽  
Single Cell ◽  
Cell Systems

scholarly journals treeclimbR pinpoints the data-dependent resolution of hierarchical hypotheses

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ruizhu Huang ◽  
Charlotte Soneson ◽  
Pierre-Luc Germain ◽  
Thomas S.B. Schmidt ◽  
Christian Von Mering ◽  
...  
Keyword(s):  
Single Cell ◽  
Synthetic Data ◽  
Cell Types ◽  
Data Driven ◽  
Rna Seq ◽  
Hierarchical Trees

AbstracttreeclimbR is for analyzing hierarchical trees of entities, such as phylogenies or cell types, at different resolutions. It proposes multiple candidates that capture the latent signal and pinpoints branches or leaves that contain features of interest, in a data-driven way. It outperforms currently available methods on synthetic data, and we highlight the approach on various applications, including microbiome and microRNA surveys as well as single-cell cytometry and RNA-seq datasets. With the emergence of various multi-resolution genomic datasets, treeclimbR provides a thorough inspection on entities across resolutions and gives additional flexibility to uncover biological associations.

scholarly journals Exemplifying the Screening Power of Mass Spectrometry Imaging over Label-Based Technologies for Simultaneous Monitoring of Drug and Metabolite Distributions in Tissue Sections

2015 ◽  
Vol 21 (2) ◽  
pp. 187-193 ◽  
Author(s):  
Richard J. A. Goodwin ◽  
Anna Nilsson ◽  
C. Logan Mackay ◽  
John G. Swales ◽  
Maria K. Johansson ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Mass Spectrometry Imaging ◽  
Cyclic Peptide ◽  
Analysis Data ◽  
Resolving Power ◽  
High Mass ◽  
Whole Body ◽  
Ion Cyclotron Resonance ◽  
Label Free ◽  
Tissue Sections

Mass spectrometry imaging (MSI) provides pharmaceutical researchers with a suite of technologies to screen and assess compound distributions and relative abundances directly from tissue sections and offer insight into drug discovery–applicable queries such as blood-brain barrier access, tumor penetration/retention, and compound toxicity related to drug retention in specific organs/cell types. Label-free MSI offers advantages over label-based assays, such as quantitative whole-body autoradiography (QWBA), in the ability to simultaneously differentiate and monitor both drug and drug metabolites. Such discrimination is not possible by label-based assays if a drug metabolite still contains the radiolabel. Here, we present data exemplifying the advantages of MSI analysis. Data of the distribution of AZD2820, a therapeutic cyclic peptide, are related to corresponding QWBA data. Distribution of AZD2820 and two metabolites is achieved by MSI, which [14C]AZD2820 QWBA fails to differentiate. Furthermore, the high mass-resolving power of Fourier transform ion cyclotron resonance MS is used to separate closely associated ions.

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