- Golub leukemia dataset
- Ritz ALL dataset
- TCGA GBM microarray dataset
- HSMM single cell RNASeq dataset
- MCF10CA single cell RNASeq dataset
This document contains results for comparing row and column sampling for consensus partitioning on the five datasets ( Golub leukemia dataset, Ritz ALL dataset and TCGA GBM microarray dataset), HSMM single cell RNASeq dataset and MCF10CA single cell RNASeq dataset. For each dataset, four consensus partitioning methods (SD:hclust, SD:skmeans, ATC:hclust and ATC:skmeans) were applied, and each method ran for 100 times so that the variability of 1-PAC can be captured. The random sampling was done by rows and by columns. Each individual cola run was done with default parameters. The scripts for the analysis can be found here.
For each dataset, there are four plots:
- boxplots that show the distributions of 1-PAC scores at each k (number of subgroups) for each method.
- mean difference of the 1-PAC score between row-sampling and column-sampling.
- heatmaps that directly show the partitions from 100 runs. Each row corresponds to one cola run and the color in the heatmap only corresponds to the subgroup labels, while not the stability of the partitioning in that run.
- barplots that show the concordance of the partitions in 100 runs for the row-sampling or for the column-sampling separately, as well as the concordance between row-sampling and column-sampling. Note the scale on y-axes is transformed as 1−√1−y.
Golub leukemia dataset
Figure S6.1. Distribution of 1-PAC scores.
Figure S6.2. Mean difference of 1-PAC between row-sampling and column-sampling.
Figure S6.3. Individual partitions from row-sampling or column-sampling.
Figure S6.4. Concordance of the partitioning by row-sampling or/and column-sampling.
Ritz ALL dataset
Figure S6.5. Distribution of 1-PAC scores.
Figure S6.6. Mean difference of 1-PAC between row-sampling and column-sampling.
Figure S6.7. Individual partitions from row-sampling or column-sampling.
Figure S6.8. Concordance of the partitioning by row-sampling or/and column-sampling.
TCGA GBM microarray dataset
Figure S6.9. Distribution of 1-PAC scores.
Figure S6.10. Mean difference of 1-PAC between row-sampling and column-sampling.
Figure S6.11. Individual partitions from row-sampling or column-sampling.
Figure S6.12. Concordance of the partitioning by row-sampling or/and column-sampling.
HSMM single cell RNASeq dataset
Figure S6.13. Distribution of 1-PAC scores.
Figure S6.14. Mean difference of 1-PAC between row-sampling and column-sampling.
Figure S6.15. Individual partitions from row-sampling or column-sampling.
Figure S6.16. Concordance of the partitioning by row-sampling or/and column-sampling.
MCF10CA single cell RNASeq dataset
Figure S6.17. Distribution of 1-PAC scores.
Figure S6.18. Mean difference of 1-PAC between row-sampling and column-sampling.
Figure S6.19. Individual partitions from row-sampling or column-sampling.
Figure S6.20. Concordance of the partitioning by row-sampling or/and column-sampling.