Statistical methods and tools for quantitative mass spectrometry-based proteomics
2020
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Advisor: Dr. Öğr. Üyesi Zeynep Filiz Eren Doğu
Abstract (EN)
Mass spectrometry, which stands out with its high sensitivity, application variety and fast results, is an indispensable tool for molecular and cellular biology to find atomic composition and sequencing over the relative masses of substances such as the clarification of the structures contained in organic and biochemical molecules, the determination of the molar masses of peptides, proteins and oligonucleotides.MSstats is an open source R package for statistical relative quantification of proteins and peptides in data dependent, targeted and data-independent proteomics. It enables the identification of different abundant proteins for MS experiments by chromatography-based quantification with complex designs, characterizing MS assays in terms of limit of blank and limit of detection (LOB/LOD), system suitability testing (SST) and quality control (QC). Users have to install R to use the MSstats package and know the R programming language or use MSstats-Shiny, which is offered online. However, many users do not know the R programming language. On the other hand, many users who know the R programming language, experience time loss during installation and coding. In addition, many users prefer to use their own computers considering the privacy of MS test results. In this thesis, a desktop application has been developed that can be used MSstats package without any programming knowledge, without installation. It can be used offline, saving user's time with ease of use, and providing privacy by analyzing on a closed local computer. This tool was developed by synchronous operation of R and Java programming languages. An interface called MSstats-J-Plugin has been prepared with Java and R programming languages.Thanks to this interface, the results are processed, made sense, visualized and finally presented to the user.Analysis of mass spectrometry data in MSstats-J-Plugin is carried out in four basic steps. These steps are "data upload", "data processing", "group comparison" and "design sample size".MSstats-J-Plugin developed as free and open-source, is designed to be accessible to everyone on the internet.
Author
Ufuk Yenigün
Institution
How to Cite
Ufuk Yenigün (Master Thesis). Statistical methods and tools for quantitative mass spectrometry-based proteomics, 2020, Muğla Sıtkı Kocman University.
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