Standardizing Proteomics Workflow for Liquid Chromatography-Mass Spectrometry: Technical and Statistical Considerations
The quantitative measurements based on liquid chromatography (LC) coupled with mass spectrometry (MS) often suffer from the problem of missing values and data heterogeneity from technical variability. We considered a proteomics data set generated from human kidney biopsy material to investigate the...
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Published in | Journal of proteomics & bioinformatics Vol. 12; no. 3; pp. 48 - 55 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
United States
2019
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Subjects | |
Online Access | Get full text |
ISSN | 0974-276X 0974-276X |
DOI | 10.35248/0974-276x.19.12.496 |
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Summary: | The quantitative measurements based on liquid chromatography (LC) coupled with mass spectrometry (MS) often suffer from the problem of missing values and data heterogeneity from technical variability. We considered a proteomics data set generated from human kidney biopsy material to investigate the technical effects of sample preparation and the quantitative MS.
We studied the effect of tissue storage methods (TSMs) and tissue extraction methods (TEMs) on data analysis. There are two TSMs: frozen (FR) and FFPE (formalin-fixed paraffin embedded); and three TEMs: MAX, TX followed by MAX and SDS followed by MAX. We assessed the impact of different strategies to analyze the data while considering heterogeneity and MVs. We have used analysis of variance (ANOVA) model to study the effects due to various sources of variability.
We found that the FFPE TSM is better than the FR TSM. We also found that the one-step TEM (MAX) is better than those of two-steps TEMs. Furthermore, we found the imputation method is a better approach than excluding the proteins with MVs or using unbalanced design. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Conceptualization of research work by SS, MM and SNR. Data analysis by SS. Interpretation of results and writing of the manuscript by SS, MM and SNR. Valuable suggestions to improve the manuscript by AR and SNR. SS was supported by Indian Council of Agricultural Research (ICAR), Ministry of Agriculture and Farmers’ Welfare, Govt. of India through ICAR-International Fellowship. SNR was supported partially by Dr. Jason Chesney, Director, James Graham Brown Cancer Center and Wendell Cherry Chair in Clinical Trial Research. Authors’ contributions |
ISSN: | 0974-276X 0974-276X |
DOI: | 10.35248/0974-276x.19.12.496 |