Pan-Cancer Biomarker Discovery CLI

Oncofind Analysis Report

Cancer Cohort TCGA-BRCA
Comparison Groupby ER_status
Group A (vs B) Positive (N=20)
Group B (vs A) Negative (N=20)
DEG Method DESEQ2

Volcano Plot Differential Expression Significance

Expression Heatmap Top Differentially Expressed Genes (Row Z-Scores)

Top Differentially Expressed Genes

Gene Log2 Fold Change P-Value Adjusted P-Value (FDR) Direction Targetable Therapy
MYC 3.0031 2.1580e-27 2.3307e-25 UP Yes (JQ1 (Clinical Trial), Molibresib (Clinical Trial))
EGFR 3.2383 8.4138e-24 4.5435e-22 UP Yes (Osimertinib, Erlotinib, Gefitinib, Cetuximab)
ESR1 4.1157 2.1583e-22 7.5055e-21 UP Yes (Tamoxifen, Fulvestrant, Elacestrant)
TP53 -3.6491 2.7798e-22 7.5055e-21 DOWN Yes (PC14586 (Clinical Trial), Kevetrin (Clinical Trial))
GENE_90 -0.1749 9.6189e-06 2.0777e-04 NS No known drugs
GENE_29 -0.1883 2.5261e-04 4.5469e-03 NS No known drugs
GENE_72 -0.1669 3.2001e-04 4.9373e-03 NS No known drugs
GENE_17 -0.1481 3.6993e-04 4.9941e-03 NS No known drugs
GENE_28 -0.1156 1.2968e-03 1.4006e-02 NS No known drugs
GENE_45 -0.1101 1.1796e-03 1.4006e-02 NS No known drugs
GENE_20 -0.1467 2.5766e-03 2.3189e-02 NS No known drugs
GENE_73 -0.1282 2.4575e-03 2.3189e-02 NS No known drugs
GENE_95 -0.1349 3.0798e-03 2.5586e-02 NS No known drugs
GENE_8 -0.1723 3.3307e-03 2.5694e-02 NS No known drugs
GENE_65 -0.1271 4.0986e-03 2.9219e-02 NS No known drugs
GENE_70 -0.1220 4.3287e-03 2.9219e-02 NS No known drugs
GENE_80 -0.1251 7.7265e-03 4.9086e-02 NS No known drugs
GENE_43 -0.1262 1.1342e-02 6.4471e-02 NS No known drugs
GENE_10 -0.1178 1.1119e-02 6.4471e-02 NS No known drugs
GENE_33 -0.1179 1.2157e-02 6.5650e-02 NS No known drugs
GENE_71 -0.1208 1.3080e-02 6.7268e-02 NS No known drugs
GENE_81 -0.1010 1.3932e-02 6.8392e-02 NS No known drugs
GENE_63 -0.1254 1.6719e-02 7.8507e-02 NS No known drugs
GENE_87 -0.1119 1.7743e-02 7.9842e-02 NS No known drugs
GENE_49 -0.1313 1.8845e-02 8.1121e-02 NS No known drugs
GENE_30 -0.0972 1.9529e-02 8.1121e-02 NS No known drugs
GENE_12 -0.1236 2.2086e-02 8.8344e-02 NS No known drugs
GENE_18 -0.1066 2.3044e-02 8.8882e-02 NS No known drugs
GENE_19 -0.0932 2.4699e-02 9.1984e-02 NS No known drugs
GENE_51 -0.1010 2.5840e-02 9.3023e-02 NS No known drugs
GENE_5 -0.1015 2.9506e-02 1.0279e-01 NS No known drugs
GENE_42 -0.1007 3.2517e-02 1.0329e-01 NS No known drugs
GENE_99 -0.0973 3.1695e-02 1.0329e-01 NS No known drugs
GENE_83 -0.0968 3.1179e-02 1.0329e-01 NS No known drugs
GENE_39 -0.1091 3.4550e-02 1.0661e-01 NS No known drugs
GENE_94 -0.0993 3.6643e-02 1.0696e-01 NS No known drugs
GENE_36 -0.0905 3.5766e-02 1.0696e-01 NS No known drugs
GENE_25 -0.1025 3.9178e-02 1.1135e-01 NS No known drugs
GENE_1 -0.1030 4.2289e-02 1.1711e-01 NS No known drugs
GENE_75 -0.1024 4.4190e-02 1.1830e-01 NS No known drugs
GENE_54 -0.0781 4.4912e-02 1.1830e-01 NS No known drugs
GENE_97 -0.0901 4.6872e-02 1.2053e-01 NS No known drugs
GENE_55 -0.0964 4.8958e-02 1.2296e-01 NS No known drugs
CDK4 -0.1017 5.3098e-02 1.3033e-01 NS Yes (Palbociclib, Ribociclib, Abemaciclib)
BRCA1 -0.0805 5.6629e-02 1.3591e-01 NS Yes (Olaparib, Niraparib, Rucaparib, Talazoparib)
GENE_77 -0.0865 5.8618e-02 1.3763e-01 NS No known drugs
GENE_23 -0.1012 6.0827e-02 1.3977e-01 NS No known drugs
GENE_48 -0.0997 6.7077e-02 1.5050e-01 NS No known drugs
GENE_57 -0.0823 6.9502e-02 1.5050e-01 NS No known drugs
GENE_91 -0.0731 6.9674e-02 1.5050e-01 NS No known drugs

Methodology Notes

Differential Expression Analysis

RNA-seq count matrices are queried from the DuckDB + Parquet local database. Counts are normalized for sequencing library depth (CPM) or processed using PyDESeq2's negative binomial Generalized Linear Model. If PyDESeq2 convergence fails or sample size is small, a fallback Welch's t-test on log-transformed counts is performed. P-values are adjusted for multiple testing using the Benjamini-Hochberg (FDR) procedure.

Batch Correction (ComBat)

If multiple sequencing plates or batches are identified in clinical metadata, an empirical location-and-scale batch correction (ComBat) is applied to prevent batch artifacts from skewing results.

Cross-Cancer Consistency Score (CCCS)

For pan-cancer gene validation, the CCCS combines Directionality (w=0.25), Fold Change Magnitude (w=0.25), Survival Significance (w=0.35), and Statistical Significance (w=0.15). Scores are scaled by the consistency ratio of significant cancer types.