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run_example.py
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run_example.py
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import gseapy
import sys, logging
rnk = "GSE4773_DEG_Expt1_Control_vs_Group1_gene.rnk"
# Run GSEA preranked - Kegg
prerank_results = gseapy.prerank(
rnk='data/rnk_lists/' + rnk,
gene_sets='data/gene_sets/c2.cp.kegg.v6.0.symbols.gmt',
outdir='out/Prerank_KEGG/' + rnk[:-4],
permutation_num=100,
no_plot=True,
processes=4
)
# Run GSEA-InContext - Kegg
gseapen_results = gseapy.incontext(
rnk='data/rnk_lists/' + rnk,
gene_sets='data/gene_sets/c2.cp.kegg.v6.0.symbols.gmt',
background_rnks='data/bg_rnk_lists/all_442_lists_permuted_x100.csv',
outdir='out/InContext_KEGG/' + rnk[:-4],
permutation_num=100,
no_plot=True,
processes=4
)
# Run GSEA preranked - Hallmarks
prerank_results = gseapy.prerank(
rnk='data/rnk_lists/' + rnk,
gene_sets='data/gene_sets/hallmarks.gmt',
outdir='out/Prerank_Hallmarks/' + rnk[:-4],
permutation_num=100,
no_plot=True,
processes=4
)
# Run GSEA-InContext - Hallmarks
gseapen_results = gseapy.incontext(
rnk='data/rnk_lists/' + rnk,
gene_sets='data/gene_sets/hallmarks.gmt',
background_rnks='data/bg_rnk_lists/all_442_lists_permuted_x100.csv',
outdir='out/InContext_Hallmarks/' + rnk[:-4],
permutation_num=100,
no_plot=True,
processes=4
)
print('Done!')