MassIVE MSV000090136

Partial Public PXD036062

The proteome landscape of genome-wide genetic perturbations

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Description

Despite the massive research efforts of the post-genomics era, a significant fraction of genes remain without functional annotation. Proteomics holds the promise to close significant gaps, but has only recently reached the scalability and precision of genome-scale studies. Here we combine large-scale proteomics with functional genomics and use a streamlined platform for fast yeast proteomics to record quantitative proteomes of ~4,500 single knock-out strains of a genome-scale yeast knock-out collection. [doi:10.25345/C5W37M06M] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: Large-scale ; genome-wide ; gene function annotation ; knock-out

Contact

Principal Investigators:
(in alphabetical order) 		Prof. Dr. Markus Ralser, Charite Universitatsmedizin Berlin, Germany
Submitting User: messnec

Publications

Christoph B. Messner, Vadim Demichev, Julia Muenzner, Simran K. Aulakh, Natalie Barthel, Annika Röhl, Lucía Herrera-Domínguez , Anna-Sophia Egger, Stephan Kamrad, Jing Hou, Guihong Tan, Oliver Lemke, Enrica Calvani, Lukasz Szyrwiel, Michael Mülleder, Kathryn S. Lilley, Charles Boone, Georg Kustatscher, Markus Ralser.
The proteomic landscape of genome-wide genetic perturbations.
Messner, Christoph B., et al. "The proteomic landscape of genome-wide genetic perturbations." Cell 186.9 (2023): 2018-2034.

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Quantification Results
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Number of distinct conditions across all analyses (original submission and reanalyses) associated with this dataset.

Distinct condition labels are counted across all files submitted in the "Metadata" category having a "Condition" column in this dataset.

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Number of distinct biological replicates across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct technical replicates across all analyses (original submission and reanalyses) associated with this dataset.

The technical replicate count is defined as the maximum number of times any one distinct combination of condition and biological replicate was analyzed across all files submitted in the "Metadata" category. In the case of fractionated experiments, only the first fraction is considered.

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Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

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Number of distinct protein accessions reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct unmodified peptide sequences reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct peptide sequences (including modified variants or peptidoforms) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Total number of peptide-spectrum matches (i.e. spectrum identifications) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct proteins quantified across all analyses (original submission and reanalyses) associated with this dataset.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

A protein is differentially abundant if its change in abundance across conditions is found to be statistically significant with an adjusted p-value <= 0.05 and lists no issues associated with statistical tests for differential abundance.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

"N/A" means no results of this type were submitted.
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