Gene set analysis methods: a systematic comparison

1 Gene set analysis methods: a systematic comparison

Mathur, R., Rotroff, D., Ma, J., Shojaie, A., & Motsinger-Reif, A. , Gene set analysis methods: a systematic comparison, 2018, BioData mining, 11(1), 8.

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1.1 Summary

Approaches for gene set analyses were assessed by using simulated data that were generated based on a real experimental data set.

1.2 Study outcomes

1.2.1 Outcome O1

The performance of ...

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

1.2.2 Outcome O2

...

Outcome O2 is presented as Figure X in the original publication.

1.2.3 Outcome On

...

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

1.2.4 Further outcomes

If intended, you can add further outcomes here.

1.3 Study design and evidence level

1.3.1 General aspects

• In this publication, the authors published a novel simulation approach termed (FANGS)
• The authors compared four different methods:
  • Gene Set Enrichment Analysis (GSEA)
  • Significance Analysis of Function and Expression (SAFE)
  • sigPathway, and
  • Correlation Adjusted Mean RAnk (CAMERA).

1.3.2 Design for Outcome O1

• The outcome was generated for ...
• Configuration parameters were chosen ...
• ...

1.3.3 Design for Outcome O2

• The outcome was generated for ...
• Configuration parameters were chosen ...
• ...

...

1.3.4 Design for Outcome O

• The outcome was generated for ...
• Configuration parameters were chosen ...
• ...

1.5 References

The list of cited or related literature is placed here.