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Table 3 Cluster parameters selected for different types of omics data in prognostic models with different covariates

From: Improving prediction performance of colon cancer prognosis based on the integration of clinical and multi-omics data

Covariates

 

Gene Expression

DNA Methylation

miRNA Expression

Gene Expression

Distance Method:

Canberra

  

Linkage Method:

Ward.D

Cluster Number:

6

DNA Methylation

Distance Method:

 

Maximum

 

Linkage Method:

Ward.D

Cluster Number:

10

miRNA Expression

Distance Method:

  

Maximum

Linkage Method:

Ward.D2

Cluster Number:

4

Clinical and Gene Expression

Distance Method:

Manhattan

  

Linkage Method:

Ward.D

Cluster Number:

4

Clinical and DNA Methylation

Distance Method:

 

Canberra

 

Linkage Method:

Ward.D

Cluster Number:

3

Clinical and miRNA Expression

Distance Method:

  

Canberra

Linkage Method:

Ward.D

Cluster Number:

3

Clinical and Gene Expression and DNA Methylation

Distance Method:

Manhattan

Correlation

 

Linkage Method:

Ward.D

Ward.D2

Cluster Number:

4

3

Clinical and Gene Expression and miRNA Expression

Distance Method:

Manhattan

 

Manhattan

Linkage Method:

Ward.D

Ward.D

Cluster Number:

4

4

Clinical and DNA Methylation and miRNA Expression

Distance Method:

 

Maximum

Canberra

Linkage Method:

Ward.D

Ward.D

Cluster Number:

10

3

Clinical and All Three Types of Omics Data

Distance Method:

Manhattan

Maximum

Manhattan

Linkage Method:

Ward.D

Ward.D

Ward.D2

Cluster Number:

4

10

4