Dataset Information

Isobaric matching between runs and novel PSM-level normalization in MaxQuant strongly improve reporter ion-based quantification - mouse tissue dataset

ABSTRACT: Isobaric labeling has the promise of combining high sample multiplexing with precise quantification. However, normalization issues and the missing value problem of complete n-plexes hamper quantification across more than one n-plex. Here we applied two novel algorithms implemented in MaxQuant that substantially improve the data analysis with multiple n-plexes. First, isobaric matching between runs (IMBR) makes use of the three-dimensional MS1 features to transfer identifications from identified to unidentified MS/MS spectra between LC-MS runs in order to utilize reporter ion intensities in unidentified spectra for quantification. On typical datasets, we observe a significant gain in quantifiable n-plexes MS/MS spectra that can be used for quantification. Second, we introduce a novel PSM-level normalization, applicable to data with and without common reference channel. It is a weighted median-based method, in which the weights reflect the number of ions that were used for fragmentation. This dataset is TMT 8-plex samples without any referene channels.

INSTRUMENT(S): LTQ Orbitrap Elite

ORGANISM(S): Mus Musculus (mouse)

TISSUE(S): Spleen, Heart, Brain, Liver, Lung, Muscle, Kidney

SUBMITTER: Sung-Huan Yu

LAB HEAD: Jürgen Cox

PROVIDER: PXD019880 | Pride | 2020-06-22

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	29May3013_DJB_mouse_tmt8_BR1_unfrac_165min_dda15_1.raw	Raw
	29May3013_DJB_mouse_tmt8_BR2_unfrac_165min_dda15_1.raw	Raw
	29May3013_DJB_mouse_tmt8_BR3_unfrac_165min_dda15_1.raw	Raw
	29May3013_DJB_mouse_tmt8_BR4_unfrac_165min_dda15_1.raw	Raw
	31May3013_DJB_mouse_tmt8_BR1_unfrac_165min_mae15_1.raw	Raw

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Publications

Isobaric Matching between Runs and Novel PSM-Level Normalization in MaxQuant Strongly Improve Reporter Ion-Based Quantification.

Yu Sung-Huan SH Kyriakidou Pelagia P Cox Jürgen J

Journal of proteome research 20200916 10

Isobaric labeling has the promise of combining high sample multiplexing with precise quantification. However, normalization issues and the missing value problem of complete n-plexes hamper quantification across more than one n-plex. Here, we introduce two novel algorithms implemented in MaxQuant that substantially improve the data analysis with multiple n-plexes. First, isobaric matching between runs makes use of the three-dimensional MS1 features to transfer identifications ...[more]

PMID: 32892627

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