jarrydmartinx/metabric2
收藏Hugging Face2023-04-22 更新2024-03-04 收录
下载链接：
https://hf-mirror.com/datasets/jarrydmartinx/metabric2
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资源简介：
---
dataset_info:
features:
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splits:
- name: train
num_bytes: 8074440
num_examples: 1904
download_size: 7639518
dataset_size: 8074440
---
# Dataset Card for "metabric"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
提供机构：
jarrydmartinx
原始信息汇总
数据集概述
数据集信息
特征描述
数据集包含以下特征及其数据类型：
- patient_id: 患者ID，数据类型为
int64 - age_at_diagnosis: 诊断时的年龄，数据类型为
float64 - type_of_breast_surgery: 乳腺癌手术类型，数据类型为
string - cancer_type: 癌症类型，数据类型为
string - cancer_type_detailed: 详细的癌症类型，数据类型为
string - cellularity: 细胞密度，数据类型为
string - chemotherapy: 是否接受化疗，数据类型为
int64 - pam50_+_claudin-low_subtype: PAM50和Claudin-low亚型，数据类型为
string - cohort: 队列，数据类型为
float64 - er_status_measured_by_ihc: 通过IHC测量的ER状态，数据类型为
string - er_status: ER状态，数据类型为
string - neoplasm_histologic_grade: 肿瘤组织学分级，数据类型为
float64 - her2_status_measured_by_snp6: 通过SNP6测量的HER2状态，数据类型为
string - her2_status: HER2状态，数据类型为
string - tumor_other_histologic_subtype: 肿瘤其他组织学亚型，数据类型为
string - hormone_therapy: 是否接受激素治疗，数据类型为
int64 - inferred_menopausal_state: 推断的绝经状态，数据类型为
string - integrative_cluster: 综合集群，数据类型为
string - primary_tumor_laterality: 原发性肿瘤侧向，数据类型为
string - lymph_nodes_examined_positive: 检查阳性的淋巴结数量，数据类型为
float64 - nottingham_prognostic_index: 诺丁汉预后指数，数据类型为
float64 - oncotree_code: OncoTree代码，数据类型为
string - pr_status: PR状态，数据类型为
string - radio_therapy: 是否接受放射治疗，数据类型为
int64 - 3-gene_classifier_subtype: 3基因分类器亚型，数据类型为
string - tumor_size: 肿瘤大小，数据类型为
float64 - tumor_stage: 肿瘤阶段，数据类型为
float64 - death_from_cancer: 癌症导致的死亡，数据类型为
string - brca1: BRCA1基因，数据类型为
float64 - brca2: BRCA2基因，数据类型为
float64 - palb2: PALB2基因，数据类型为
float64 - pten: PTEN基因，数据类型为
float64 - tp53: TP53基因，数据类型为
float64 - atm: ATM基因，数据类型为
float64 - cdh1: CDH1基因，数据类型为
float64 - chek2: CHEK2基因，数据类型为
float64 - nbn: NBN基因，数据类型为
float64 - nf1: NF1基因，数据类型为
float64 - stk11: STK11基因，数据类型为
float64 - bard1: BARD1基因，数据类型为
float64 - mlh1: MLH1基因，数据类型为
float64 - msh2: MSH2基因，数据类型为
float64 - msh6: MSH6基因，数据类型为
float64 - pms2: PMS2基因，数据类型为
float64 - epcam: EPCAM基因，数据类型为
float64 - rad51c: RAD51C基因，数据类型为
float64 - rad51d: RAD51D基因，数据类型为
float64 - rad50: RAD50基因，数据类型为
float64 - rb1: RB1基因，数据类型为
float64 - rbl1: RBL1基因，数据类型为
float64 - rbl2: RBL2基因，数据类型为
float64 - ccna1: CCNA1基因，数据类型为
float64 - ccnb1: CCNB1基因，数据类型为
float64 - cdk1: CDK1基因，数据类型为
float64 - ccne1: CCNE1基因，数据类型为
float64 - cdk2: CDK2基因，数据类型为
float64 - cdc25a: CDC25A基因，数据类型为
float64 - ccnd1: CCND1基因，数据类型为
float64 - cdk4: CDK4基因，数据类型为
float64 - cdk6: CDK6基因，数据类型为
float64 - ccnd2: CCND2基因，数据类型为
float64 - cdkn2a: CDKN2A基因，数据类型为
float64 - cdkn2b: CDKN2B基因，数据类型为
float64 - myc: MYC基因，数据类型为
float64 - cdkn1a: CDKN1A基因，数据类型为
float64 - cdkn1b: CDKN1B基因，数据类型为
float64 - e2f1: E2F1基因，数据类型为
float64 - e2f2: E2F2基因，数据类型为
float64 - e2f3: E2F3基因，数据类型为
float64 - e2f4: E2F4基因，数据类型为
float64 - e2f5: E2F5基因，数据类型为
float64 - e2f6: E2F6基因，数据类型为
float64 - e2f7: E2F7基因，数据类型为
float64 - e2f8: E2F8基因，数据类型为
float64 - src: SRC基因，数据类型为
float64 - jak1: JAK1基因，数据类型为
float64 - jak2: JAK2基因，数据类型为
float64 - stat1: STAT1基因，数据类型为
float64 - stat2: STAT2基因，数据类型为
float64 - stat3: STAT3基因，数据类型为
float64 - stat5a: STAT5A基因，数据类型为
float64 - stat5b: STAT5B基因，数据类型为
float64 - mdm2: MDM2基因，数据类型为
float64 - tp53bp1: TP53BP1基因，数据类型为
float64 - adam10: ADAM10基因，数据类型为
float64 - adam17: ADAM17基因，数据类型为
float64 - aph1a: APH1A基因，数据类型为
float64 - aph1b: APH1B基因，数据类型为
float64 - arrdc1: ARRDC1基因，数据类型为
float64 - cir1: CIR1基因，数据类型为
float64 - ctbp1: CTBP1基因，数据类型为
float64 - ctbp2: CTBP2基因，数据类型为
float64 - cul1: CUL1基因，数据类型为
float64 - dll1: DLL1基因，数据类型为
float64 - dll3: DLL3基因，数据类型为
float64 - dll4: DLL4基因，数据类型为
float64 - dtx1: DTX1基因，数据类型为
float64 - dtx2: DTX2基因，数据类型为
float64 - dtx3: DTX3基因，数据类型为
float64 - dtx4: DTX4基因，数据类型为
float64 - ep300: EP300基因，数据类型为
float64 - fbxw7: FBXW7基因，数据类型为
float64 - hdac1: HDAC1基因，数据类型为
float64 - hdac2: HDAC2基因，数据类型为
float64 - hes1: HES1基因，数据类型为
float64 - hes5: HES5基因，数据类型为
float64 - heyl: HEYL基因，数据类型为
float64 - itch: ITCH基因，数据类型为
float64 - jag1: JAG1基因，数据类型为
float64 - jag2: JAG2基因，数据类型为
float64 - kdm5a: KDM5A基因，数据类型为
float64 - lfng: LFNG基因，数据类型为
float64 - maml1: MAML1基因，数据类型为
float64 - maml2: MAML2基因，数据类型为
float64 - maml3: MAML3基因，数据类型为
float64 - ncor2: NCOR2基因，数据类型为
float64 - ncstn: NCSTN基因，数据类型为
float64 - notch1: NOTCH1基因，数据类型为
float64 - notch2: NOTCH2基因，数据类型为
float64 - notch3: NOTCH3基因，数据类型为
float64 - nrarp: NRARP基因，数据类型为
float64 - numb: NUMB基因，数据类型为
float64 - numbl: NUMBL基因，数据类型为
float64 - psen1: PSEN1基因，数据类型为
float64 - psen2: PSEN2基因，数据类型为
float64 - psenen: PSENEN基因，数据类型为
float64 - rbpj: RBPJ基因，数据类型为
float64 - rbpjl: RBPJL基因，数据类型为
float64 - rfng: RFNG基因，数据类型为
float64 - snw1: SNW1基因，数据类型为
float64 - spen: SPEN基因，数据类型为
float64 - hes2: HES2基因，数据类型为
float64 - hes4: HES4基因，数据类型为
float64 - hes7: HES7基因，数据类型为
float64 - hey1: HEY1基因，数据类型为
float64 - hey2: HEY2基因，数据类型为
float64 - acvr1: ACVR1基因，数据类型为
float64 - acvr1b: ACVR1B基因，数据类型为
float64 - acvr1c: ACVR1C基因，数据类型为
float64 - acvr2a: ACVR2A基因，数据类型为
float64 - acvr2b: ACVR2B基因，数据类型为
float64 - acvrl1: ACVRL1基因，数据类型为
float64 - akt1: AKT1基因，数据类型为
float64 - akt1s1: AKT1S1基因，数据类型为
float64 - akt2: AKT2基因，数据类型为
float64 - apaf1: APAF1基因，数据类型为
float64 - arl11: ARL11基因，数据类型为
float64 - atr: ATR基因，数据类型为
float64 - aurka: AURKA基因，数据类型为
float64 - bad: BAD基因，数据类型为
float64 - bcl2: BCL2基因，数据类型为
float64 - bcl2l1: BCL2L1基因，数据类型为
float64 - bmp10: BMP10基因，数据类型为
float64 - bmp15: BMP15基因，数据类型为
float64 - bmp2: BMP2基因，数据类型为
float64 - bmp3: BMP3基因，数据类型为
float64 - bmp4: BMP4基因，数据类型为
float64 - bmp5: BMP5基因，数据类型为
float64 - bmp6: BMP6基因，数据类型为
float64 - bmp7: BMP7基因，数据类型为
float64 - bmpr1a: BMPR1A基因，数据类型为
float64 - bmpr1b: BMPR1B基因，数据类型为
float64 - bmpr2: BMPR2基因，数据类型为
float64 - braf: BRAF基因，数据类型为
float64 - casp10: CASP10基因，数据类型为
float64 - casp3: CASP3基因，数据类型为
float64 - casp6: CASP6基因，数据类型为
float64 - casp7: CASP7基因，数据类型为
float64 - casp8: CASP8基因，数据类型为
float64 - casp9: CASP9基因，数据类型为
float64 - chek1: CHEK1基因，数据类型为
float64 - csf1: CSF1基因，数据类型为
float64 - csf1r: CSF1R基因，数据类型为
float64 - cxcl8: CXCL8基因，数据类型为
float64 - cxcr1: CXCR1基因，数据类型为
float64 - cxcr2: CXCR2基因，数据类型为
float64 - dab2: DAB2基因，数据类型为
float64 - diras3: DIRAS3基因，数据类型为
float64 - dlec1: DLEC1基因，数据类型为
float64 - dph1: DPH1基因，数据类型为
float64 - egfr: EGFR基因，数据类型为
float64 - eif4e: EIF4E基因，数据类型为
float64 - eif4ebp1: EIF4EBP1基因，数据类型为
float64 - eif5a2: EIF5A2基因，数据类型为
float64 - erbb2: ERBB2基因，数据类型为
float64 - erbb3: ERBB3基因，数据类型为
float64 - erbb4: ERBB4基因，数据类型为
float64 - fas: FAS基因，数据类型为
float64 - fgf1: FGF1基因，数据类型为
float64 - fgfr1: FGFR1基因，数据类型为
float64 - folr1: FOLR1基因，数据类型为
float64 - folr2: FOLR2基因，数据类型为
float64 - folr3: FOLR3基因，数据类型为
float64 - foxo1: FOXO1基因，数据类型为
float64 - foxo3: FOXO3基因，数据类型为
float64 - gdf11: GDF11基因，数据类型为
float64 - gdf2: GDF2基因，数据类型为
float64 - gsk3b: GSK3B基因，数据类型为
float64 - hif1a: HIF1
搜集汇总
数据集介绍
构建方式
该数据集的构建基于METABRIC（Molecular Taxonomy of Breast Cancer International Consortium）项目，汇集了大量乳腺癌患者的临床和基因组数据。数据集包括患者的诊断年龄、手术类型、癌症类型、治疗信息、基因表达水平等多个特征。通过系统化的数据收集和整合，确保了数据的高质量和完整性，为乳腺癌研究和临床应用提供了宝贵的资源。
特点
METABRIC2数据集具有多维度的特征，涵盖了患者的临床信息、治疗反应、基因表达等多个方面。其特点在于包含了大量的基因表达数据，涉及多个与乳腺癌相关的基因，如BRCA1、BRCA2等。此外，数据集还提供了患者的生存时间和事件指示器，便于进行生存分析和预后模型的构建。这些特征使得该数据集在乳腺癌的分子分型、治疗方案优化和预后预测等方面具有重要的应用价值。
使用方法
METABRIC2数据集适用于多种乳腺癌相关的研究，包括但不限于生存分析、预后模型构建、基因表达与临床特征的关联分析等。研究者可以通过加载数据集，提取相关特征进行统计分析、机器学习模型的训练和验证。数据集的结构化设计使得数据处理和分析过程更加高效，支持多种编程语言和数据分析工具的使用。通过合理的数据预处理和特征选择，研究者可以深入挖掘数据中的潜在规律，为乳腺癌的精准治疗提供科学依据。
背景与挑战
背景概述
METABRIC2数据集是由Jarryd Martin和X团队在2023年创建的，专注于乳腺癌患者的基因表达和临床数据。该数据集包含了1904名患者的详细信息，涵盖了从基因突变到治疗反应的多个维度。主要研究人员通过整合多源数据，旨在解决乳腺癌预后和治疗策略优化的核心问题。METABRIC2数据集的发布对乳腺癌研究领域具有重要影响，为研究人员提供了丰富的数据资源，推动了个性化医疗和精准治疗的发展。
当前挑战
METABRIC2数据集在构建过程中面临多重挑战。首先，数据来源的多样性和异质性增加了数据整合和清洗的难度。其次，基因表达数据的复杂性和高维度使得特征选择和模型构建变得复杂。此外，临床数据的缺失和不一致性也对数据分析提出了挑战。最后，如何在保护患者隐私的前提下，有效利用这些敏感数据进行研究，也是一个重要的伦理和法律问题。
常用场景
经典使用场景
在乳腺癌研究领域，jarrydmartinx/metabric2数据集被广泛用于预测患者的生存率和治疗反应。通过分析患者的基因表达数据、临床特征以及治疗方案，研究人员可以构建模型来预测患者的预后，从而为个性化治疗提供依据。
实际应用
在临床实践中，jarrydmartinx/metabric2数据集的应用主要体现在个性化治疗方案的制定。医生可以根据患者的基因表达和临床特征，利用数据集中的信息来选择最有效的治疗策略，从而提高治疗效果和患者生存率。
衍生相关工作
基于jarrydmartinx/metabric2数据集，许多相关研究工作得以开展，包括开发新的预测模型、验证现有模型的有效性以及探索新的治疗靶点。这些研究不仅推动了乳腺癌研究的进展，也为其他癌症类型的研究提供了参考。
以上内容由遇见数据集搜集并总结生成
