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Fig. 4 | Genome Biology

Fig. 4

From: DeepMILO: a deep learning approach to predict the impact of non-coding sequence variants on 3D chromatin structure

Fig. 4

Application of DeepMILO on patient samples. LMS, soft tissue cancer—leiomyosarcoma; SKCA, skin adenocarcinoma; MELA, skin cancer; BTCA, biliary tract cancer; ESAD, esophageal adenocarcinoma; LIRI, liver cancer; OV, ovarian cancer; RECA, renal cell cancer; MALY, malignant lymphoma; PACA, pancreatic cancer; BRCA, breast ER+ and HER2− cancer; BOCA, soft tissue cancer—Ewing sarcoma. a Number of disrupted insulator loops in ICGC cohorts. b Mutation burden in ICGC cohorts. c, d Oncogenes BCL2 and MYC show differential expression between patients with decrease in loop probability and other patients (MALY cohort, Wilcoxon signed-rank test)

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