Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies

Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies

Lazar, C., Gatto, L., Ferro, M., Bruley, C., and Burger, T. (2016): Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies. Journal of Proteome Research, 15:1116–1125.

https://doi.org/10.1021/acs.jproteome.5b00981

Summary

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Study outcomes

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Outcome O1

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Outcome O2

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Outcome On

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Further outcomes

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Study design and evidence level

General aspects

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Design for Outcome O1

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Design for Outcome O2

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...

Design for Outcome O

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References

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