Add resplitter.py

README.md

@@ -62,12 +62,25 @@ mv tcga* data
 
 #### Data splits generation
 
-To recreate the 10 data splits, run the following commands in a shell:
+To recreate the 10 data splits, first run the following commands in a shell:
 
 ```bash
 Rscript scripts/prepare_ACGT.R --tumor aml --suffix 03 --datadir data/original/Shamir_lab --outdir data/tcga_aml
 Rscript scripts/prepare_ACGT.R --tumor kidney --suffix 01 --datadir data/original/Shamir_lab --outdir data/tcga_kirc
 Rscript scripts/prepare_BRCA.R --task ER --datadir data/original --outdir data/tcga_brca
+Rscript scripts/prepare_BRCA.R --task subtypes --datadir data/original --outdir data/tcga_brca
+```
+
+This creates 10 TR/TS partitions, with ID 0 to 9. To further partition into the 10 TR/TS/TS2 splits described in the paper, with ID 50 to 59 (you can use any other IDs), run in a shell:
+
+```bash
+for dataset in tcga_aml tcga_kirc; do
+    python resplitter.py --datafolder data/$dataset --target OS --n_splits_start 0 --n_splits_end 10 --split_offset 50
+done
+
+for target in ER subtypes; do
+    python resplitter.py --datafolder data/tcga_breast --target $target --n_splits_start 0 --n_splits_end 10 --split_offset 50
+done
 ```
 
 #### Input files