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 == Cosmin Lazar, Laurent Gatto, Myriam Ferro, Christophe Bruley and Thomas Burger (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.

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1 Summary

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2 Study outcomes

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2.1 Outcome O1

The performance of ...

Outcome O1 is presented as Figure X in the original publication.

2.2 Outcome O2

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2.3 Outcome On

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Outcome On is presented as Figure X in the original publication.

2.4 Further outcomes

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3 Study design and evidence level

3.1 General aspects

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3.2 Design for Outcome O1

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• Configuration parameters were chosen ...
• ...

3.3 Design for Outcome O2

• The outcome was generated for ...
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• ...

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3.4 Design for Outcome O

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• Configuration parameters were chosen ...
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5 References

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