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Optimising multi-batch TMT analysis to mitigate inflation of missing values, false positives and diminished inter batch accuracy

View ORCID ProfileAlejandro Brenes, Jens Hukelmann, Dalila Bensaddek, Angus I. Lamond
doi: https://doi.org/10.1101/497396
Alejandro Brenes
1Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow St, Dundee, DD1 5EH, United Kingdom
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  • ORCID record for Alejandro Brenes
Jens Hukelmann
1Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow St, Dundee, DD1 5EH, United Kingdom
2Immatics, Paul-Ehrlich-Str. 15, Tuebingen, 72076, Germany
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Dalila Bensaddek
3Bruker Daltonics Inc, Banner Lane, Coventry, CV4 9GH, United Kingdom
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Angus I. Lamond
1Centre for Gene Regulation and Expression, School of Life Sciences, University of Dundee, Dow St, Dundee, DD1 5EH, United Kingdom
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Abstract

Multiplexing strategies for large-scale proteomic analyses have become increasingly prevalent, TMT in particular. Here we used a large iPSC proteomic experiment with twenty-four 10-plex TMT batches to evaluate the effect of integrating multiple TMT batches within a single analysis. We reveal a significant inflation rate of missing protein and peptide values and show that precision decreases as multiple batches are integrated. Additionally, we explore the effect of false positives using Y chromosome specific peptides as an internal control to quantify the effect of co-isolation interference, as well as primary and secondary reporter ion interference. Based on the results we suggest solutions to mitigate these effects. We show using a reference line can increase precision by normalising the quantification across batches and we propose experimental designs that minimise the effect of cross population reporter ion interference.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted December 16, 2018.
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Optimising multi-batch TMT analysis to mitigate inflation of missing values, false positives and diminished inter batch accuracy
Alejandro Brenes, Jens Hukelmann, Dalila Bensaddek, Angus I. Lamond
bioRxiv 497396; doi: https://doi.org/10.1101/497396
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Optimising multi-batch TMT analysis to mitigate inflation of missing values, false positives and diminished inter batch accuracy
Alejandro Brenes, Jens Hukelmann, Dalila Bensaddek, Angus I. Lamond
bioRxiv 497396; doi: https://doi.org/10.1101/497396

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