Created
August 19, 2025 19:54
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get pairwise DE genes for each gene in the set
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Target: CHMP3, DE genes: 3508 | |
Target: AKT2, DE genes: 908 | |
Target: SHPRH, DE genes: 121 | |
Target: TMSB4X, DE genes: 291 | |
Target: KLF10, DE genes: 6500 | |
Target: TARBP2, DE genes: 1073 | |
Target: KDM2B, DE genes: 4582 | |
Target: non-targeting, DE genes: 0 | |
Target: SV2A, DE genes: 198 | |
Target: CLDN6, DE genes: 124 | |
Target: TCF3, DE genes: 486 | |
Target: ANTXR1, DE genes: 25 | |
Target: NDUFB6, DE genes: 1689 | |
Target: TADA1, DE genes: 10835 | |
Target: MED12, DE genes: 5982 | |
Target: CAMSAP2, DE genes: 25 | |
Target: IDE, DE genes: 119 | |
Target: PRCP, DE genes: 134 | |
Target: WFS1, DE genes: 55 | |
Target: FOXH1, DE genes: 1742 | |
Target: SMARCA4, DE genes: 11415 | |
Target: TWF2, DE genes: 45 | |
Target: SAFB, DE genes: 4608 | |
Target: POLB, DE genes: 1624 | |
Target: TSC22D4, DE genes: 2849 | |
Target: ACVR1B, DE genes: 1670 | |
Target: PMS1, DE genes: 38 | |
Target: NISCH, DE genes: 3518 | |
Target: INSIG1, DE genes: 7556 | |
Target: DHCR24, DE genes: 714 | |
Target: MAP3K7, DE genes: 269 | |
Target: TMSB10, DE genes: 4808 | |
Target: SMARCA5, DE genes: 10392 | |
Target: STAG2, DE genes: 8040 | |
Target: ZNF426, DE genes: 56 | |
Target: DNMT1, DE genes: 10389 | |
Target: SSBP1, DE genes: 3452 | |
Target: HIRA, DE genes: 3382 | |
Target: USP22, DE genes: 3607 | |
Target: PBX1, DE genes: 302 | |
Target: EID2, DE genes: 50 | |
Target: KAT2A, DE genes: 10791 | |
Target: MAPKAPK2, DE genes: 66 | |
Target: SRC, DE genes: 574 | |
Target: HSBP1, DE genes: 1416 | |
Target: MED13, DE genes: 6401 | |
Target: ZNF593, DE genes: 1628 | |
Target: TET1, DE genes: 2513 | |
Target: KDR, DE genes: 62 | |
Target: EIF4B, DE genes: 6385 | |
Target: SIX4, DE genes: 343 | |
Target: TFAM, DE genes: 6083 | |
Target: MAST2, DE genes: 121 | |
Target: SMAGP, DE genes: 1886 | |
Target: CAST, DE genes: 4802 | |
Target: MTA1, DE genes: 2781 | |
Target: ATP1B1, DE genes: 34 | |
Target: KIF20A, DE genes: 5879 | |
Target: KIF1B, DE genes: 86 | |
Target: NCK2, DE genes: 37 | |
Target: XRCC4, DE genes: 4013 | |
Target: RNF2, DE genes: 9405 | |
Target: CASP3, DE genes: 8088 | |
Target: HMGN1, DE genes: 47 | |
Target: GSK3B, DE genes: 4039 | |
Target: RAB3B, DE genes: 28 | |
Target: MED13L, DE genes: 2331 | |
Target: HMGB2, DE genes: 6261 | |
Target: DHX36, DE genes: 10814 | |
Target: IGF2R, DE genes: 227 | |
Target: HAT1, DE genes: 1232 | |
Target: STAT6, DE genes: 1650 | |
Target: ARID1A, DE genes: 5800 | |
Target: CDCA2, DE genes: 1160 | |
Target: SNCA, DE genes: 336 | |
Target: TRAM2, DE genes: 278 | |
Target: STAT1, DE genes: 65 | |
Target: TMBIM6, DE genes: 155 | |
Target: PMEL, DE genes: 346 | |
Target: DAXX, DE genes: 1973 | |
Target: PRDM14, DE genes: 10856 | |
Target: NREP, DE genes: 5897 | |
Target: CREG1, DE genes: 84 | |
Target: METTL14, DE genes: 11003 | |
Target: RAF1, DE genes: 880 | |
Target: RRM1, DE genes: 1096 | |
Target: UQCRQ, DE genes: 3113 | |
Target: BIRC2, DE genes: 6182 | |
Target: IKBKG, DE genes: 467 | |
Target: LRPPRC, DE genes: 5395 | |
Target: SDC1, DE genes: 601 | |
Target: ZNF714, DE genes: 64 | |
Target: CASP2, DE genes: 137 | |
Target: STX4, DE genes: 1809 | |
Target: IRF3, DE genes: 77 | |
Target: CENPO, DE genes: 2155 | |
Target: EWSR1, DE genes: 7143 | |
Target: PLCB3, DE genes: 1749 | |
Target: PHF14, DE genes: 1757 | |
Target: MAU2, DE genes: 8741 | |
Target: TAZ, DE genes: 341 | |
Target: DLG5, DE genes: 1690 | |
Target: CLDN7, DE genes: 719 | |
Target: PAGR1, DE genes: 2025 | |
Target: PTPN1, DE genes: 43 | |
Target: NDUFB4, DE genes: 2586 | |
Target: KDM1A, DE genes: 11779 | |
Target: UBE3C, DE genes: 5966 | |
Target: TGFBR2, DE genes: 7742 | |
Target: TRAPPC6A, DE genes: 2725 | |
Target: MED24, DE genes: 7290 | |
Target: METTL17, DE genes: 7103 | |
Target: DZIP3, DE genes: 40 | |
Target: SOX2, DE genes: 8761 | |
Target: ZNF286A, DE genes: 42 | |
Target: MKI67, DE genes: 320 | |
Target: TXNDC9, DE genes: 1984 | |
Target: MAP1B, DE genes: 53 | |
Target: ACAT2, DE genes: 6878 | |
Target: PRR12, DE genes: 2964 | |
Target: TAF13, DE genes: 5444 | |
Target: LAD1, DE genes: 16 | |
Target: CALM3, DE genes: 1773 | |
Target: C1QBP, DE genes: 5628 | |
Target: NRAS, DE genes: 105 | |
Target: SALL4, DE genes: 4819 | |
Target: MED1, DE genes: 5232 | |
Target: NIT1, DE genes: 10063 | |
Target: MBTPS1, DE genes: 6013 | |
Target: ATP6V0B, DE genes: 156 | |
Target: ZNF562, DE genes: 104 | |
Target: PHF10, DE genes: 2451 | |
Target: WSB2, DE genes: 3824 | |
Target: FDPS, DE genes: 3598 | |
Target: SIN3B, DE genes: 8765 | |
Target: METTL3, DE genes: 10991 | |
Target: SLC25A3, DE genes: 1924 | |
Target: OXCT1, DE genes: 3605 | |
Target: LZTR1, DE genes: 5948 | |
Target: SLC39A6, DE genes: 7378 | |
Target: RNF20, DE genes: 5284 | |
Target: SEC62, DE genes: 5620 | |
Target: EPB41L2, DE genes: 4626 | |
Target: OXA1L, DE genes: 2218 | |
Target: ATP6V0C, DE genes: 256 | |
Target: ETV4, DE genes: 3658 | |
Target: EPHB4, DE genes: 3203 | |
Target: BRD9, DE genes: 443 | |
Target: SUPT4H1, DE genes: 10190 | |
Target: ATM, DE genes: 5152 | |
Target: DNAJA3, DE genes: 2352 |
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# /// script | |
# requires-python = ">=3.10" | |
# dependencies = [ | |
# "anndata", | |
# "pdex", | |
# ] | |
# | |
# [tool.uv.sources] | |
# pdex = { git = "https://github.com/drbh/pdex.git", branch = "pairwise_fdr" } | |
# /// | |
import os | |
import anndata as ad | |
from pdex._single_cell import ( | |
parallel_differential_expression_vec_wrapper as parallel_differential_expression, | |
) | |
adata = ad.read_h5ad("../bspc/convert/vcc_data/adata_Training.h5ad") | |
os.makedirs("de_results", exist_ok=True) | |
ctrl_mask = adata.obs["target_gene"] == "non-targeting" | |
control_cells = adata[ctrl_mask] | |
# get all unique target genes | |
targets = adata.obs["target_gene"].unique() | |
results = parallel_differential_expression( | |
# de_adata, | |
adata, | |
reference="non-targeting", | |
groupby_key="target_gene", | |
) | |
results["diff"] = results["pairwise_fdr"] - results["fdr"] | |
results = results.sort_values("diff") | |
filtered = results[results["pairwise_fdr"] < 0.05] | |
# save filtered results | |
filtered.to_csv("de_results/filtered_results.csv") | |
print(filtered) | |
# print the number of each target | |
for target in targets: | |
count = filtered[filtered["target"] == target].shape[0] | |
print(f"Target: {target}, DE genes: {count}") |
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