NRF1 and NRF1 target genes and aggressive Breast Cancer

[zgong001]

For the analysis 3 of above Breast Cancer Analysis: 3. Luminal A {White, Asian, Hispanic, Black} x {rest}, the attachments are the sub-datasets. The datasets are { Luminal A , pairwised(Hispanic, Asian, Black, White)}, and the 18 genes which is most correlative with the ETHNICITY.

[zgong001]

For the analysis 4 of above Breast Cancer Analysis:4. Luminal B {White, Asian, Hispanic, Black} x {rest}, the attachments are the sub-datasets. The datasets are { Luminal B , pairwised(Hispanic, Asian, Black, White)}, and the 18 genes which is most correlative with the ETHNICITY.

[zgong001]

For the analysis 5 of above Breast Cancer Analysis: 5. HER2 {White, Asian, Hispanic, Black} x {rest}, the attachments are the sub-datasets. The datasets are { HER2 , pairwised(Asian, Black, White)}, and the 18 genes which is most correlative with the ETHNICITY.

For disease HER2, there is no Hispanic.

[zgong001]

The attachments are the raw results of running c++ ordering code.

[cwyoo]

The attachments are the raw results of running c++ ordering code.

In the results,

11 16 15 17 18 0 19 3 13 7 1 10 6 9 14 8 2 12 4 5 -38.519928808747494 { } 0.5
18 16 15 17 11 0 19 3 13 7 1 10 6 9 14 8 2 12 4 5 -38.519928808747494 {0.5} 0.19683057967672635

how can two same order score receive different percentage score?

[zgong001]

I don't know why they are different. I didn't check Efrain's code. They should be same. You don't need worry about the percent. In the R result, you will see the correct percent.

[zgong001]

The attachments are the orders, first 20 structures with orders and without orders.

Added Consensus Structures.

[zgong001]

The attachments are the orders, first 20 structures with orders and without orders.

[zgong001]

The attachments are the orders, first 20 structures with orders and without orders.

Added Consensus Structures.

[zgong001]

The attachments are the orders, first 20 structures with orders and without orders.