cosmic-database

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COSMIC Database

COSMIC数据库

Overview

概述

COSMIC (Catalogue of Somatic Mutations in Cancer) is the world's largest and most comprehensive database for exploring somatic mutations in human cancer. Access COSMIC's extensive collection of cancer genomics data, including millions of mutations across thousands of cancer types, curated gene lists, mutational signatures, and clinical annotations programmatically.

COSMIC（Catalogue of Somatic Mutations in Cancer）是全球规模最大、最全面的人类癌症体细胞突变探索数据库。你可以通过编程方式访问COSMIC丰富的癌症基因组数据，涵盖数千种癌症类型的数百万个突变、经过专家整理的基因列表、突变特征以及临床注释信息。

When to Use This Skill

何时使用该技能

This skill should be used when:

Downloading cancer mutation data from COSMIC
Accessing the Cancer Gene Census for curated cancer gene lists
Retrieving mutational signature profiles
Querying structural variants, copy number alterations, or gene fusions
Analyzing drug resistance mutations
Working with cancer cell line genomics data
Integrating cancer mutation data into bioinformatics pipelines
Researching specific genes or mutations in cancer contexts

当你有以下需求时，可使用本技能：

从COSMIC下载癌症突变数据
访问癌症基因普查（Cancer Gene Census）获取经过专家整理的癌症基因列表
检索突变特征图谱
查询结构变异、拷贝数改变或基因融合数据
分析耐药突变
处理癌细胞系基因组数据
将癌症突变数据整合到生物信息学流程中
在癌症研究场景下探究特定基因或突变

Prerequisites

前提条件

Account Registration

账户注册

COSMIC requires authentication for data downloads:

Academic users: Free access with registration at https://cancer.sanger.ac.uk/cosmic/register
Commercial users: License required (contact QIAGEN)

COSMIC的数据下载需要身份验证：

学术用户：注册后可免费访问，注册地址：https://cancer.sanger.ac.uk/cosmic/register
商业用户：需要获取授权许可（联系QIAGEN）

Python Requirements

Python环境要求

bash

uv pip install requests pandas

bash

uv pip install requests pandas

Quick Start

快速开始

1. Basic File Download

1. 基础文件下载

Use the

scripts/download_cosmic.py

script to download COSMIC data files:

python

from scripts.download_cosmic import download_cosmic_file

使用

scripts/download_cosmic.py

脚本下载COSMIC数据文件：

python

from scripts.download_cosmic import download_cosmic_file

Download mutation data

下载突变数据

download_cosmic_file( email="your_email@institution.edu", password="your_password", filepath="GRCh38/cosmic/latest/CosmicMutantExport.tsv.gz", output_filename="cosmic_mutations.tsv.gz" )

undefined

download_cosmic_file( email="your_email@institution.edu", password="your_password", filepath="GRCh38/cosmic/latest/CosmicMutantExport.tsv.gz", output_filename="cosmic_mutations.tsv.gz" )

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2. Command-Line Usage

2. 命令行使用方式

bash

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bash

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Download using shorthand data type

使用简写数据类型下载

python scripts/download_cosmic.py user@email.com --data-type mutations

Download specific file

下载特定文件

python scripts/download_cosmic.py user@email.com
--filepath GRCh38/cosmic/latest/cancer_gene_census.csv

Download for specific genome assembly

针对特定基因组组装版本下载

python scripts/download_cosmic.py user@email.com
--data-type gene_census --assembly GRCh37 -o cancer_genes.csv

undefined

python scripts/download_cosmic.py user@email.com
--data-type gene_census --assembly GRCh37 -o cancer_genes.csv

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3. Working with Downloaded Data

3. 处理已下载的数据

python

import pandas as pd

python

import pandas as pd

Read mutation data

读取突变数据

mutations = pd.read_csv('cosmic_mutations.tsv.gz', sep='\t', compression='gzip')

Read Cancer Gene Census

读取癌症基因普查数据

gene_census = pd.read_csv('cancer_gene_census.csv')

Read VCF format

读取VCF格式数据

import pysam vcf = pysam.VariantFile('CosmicCodingMuts.vcf.gz')

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import pysam vcf = pysam.VariantFile('CosmicCodingMuts.vcf.gz')

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Available Data Types

可用数据类型

Core Mutations

核心突变数据

Download comprehensive mutation data including point mutations, indels, and genomic annotations.

Common data types:

```
mutations
```
- Complete coding mutations (TSV format)
```
mutations_vcf
```
- Coding mutations in VCF format
```
sample_info
```
- Sample metadata and tumor information

python

undefined

下载包含点突变、插入缺失以及基因组注释信息的全面突变数据。

常见数据类型：

```
mutations
```
- 完整编码区突变（TSV格式）
```
mutations_vcf
```
- VCF格式的编码区突变
```
sample_info
```
- 样本元数据和肿瘤信息

python

undefined

Download all coding mutations

下载所有编码区突变数据

download_cosmic_file( email="user@email.com", password="password", filepath="GRCh38/cosmic/latest/CosmicMutantExport.tsv.gz" )

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download_cosmic_file( email="user@email.com", password="password", filepath="GRCh38/cosmic/latest/CosmicMutantExport.tsv.gz" )

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Cancer Gene Census

癌症基因普查

Access the expert-curated list of ~700+ cancer genes with substantial evidence of cancer involvement.

python

undefined

访问由专家整理的约700+个癌症基因列表，这些基因均有充分证据表明与癌症相关。

python

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Download Cancer Gene Census

下载癌症基因普查数据

download_cosmic_file( email="user@email.com", password="password", filepath="GRCh38/cosmic/latest/cancer_gene_census.csv" )


**Use cases**:
- Identifying known cancer genes
- Filtering variants by cancer relevance
- Understanding gene roles (oncogene vs tumor suppressor)
- Target gene selection for research

download_cosmic_file( email="user@email.com", password="password", filepath="GRCh38/cosmic/latest/cancer_gene_census.csv" )


**使用场景**：
- 识别已知癌症基因
- 根据癌症相关性过滤变异位点
- 了解基因作用（癌基因vs抑癌基因）
- 为研究选择目标基因

Mutational Signatures

突变特征

Download signature profiles for mutational signature analysis.

python

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下载突变特征图谱用于突变特征分析。

python

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Download signature definitions

下载突变特征定义文件

download_cosmic_file( email="user@email.com", password="password", filepath="signatures/signatures.tsv" )


**Signature types**:
- Single Base Substitution (SBS) signatures
- Doublet Base Substitution (DBS) signatures
- Insertion/Deletion (ID) signatures

download_cosmic_file( email="user@email.com", password="password", filepath="signatures/signatures.tsv" )


**特征类型**：
- 单碱基替换（SBS）特征
- 双碱基替换（DBS）特征
- 插入/缺失（ID）特征

Structural Variants and Fusions

结构变异与融合基因

Access gene fusion data and structural rearrangements.

Available data types:

```
structural_variants
```
- Structural breakpoints
```
fusion_genes
```
- Gene fusion events

python

undefined

访问基因融合数据和结构重排信息。

可用数据类型：

```
structural_variants
```
- 结构断点数据
```
fusion_genes
```
- 基因融合事件数据

python

undefined

Download gene fusions

下载基因融合数据

download_cosmic_file( email="user@email.com", password="password", filepath="GRCh38/cosmic/latest/CosmicFusionExport.tsv.gz" )

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download_cosmic_file( email="user@email.com", password="password", filepath="GRCh38/cosmic/latest/CosmicFusionExport.tsv.gz" )

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Copy Number and Expression

拷贝数与表达数据

Retrieve copy number alterations and gene expression data.

Available data types:

```
copy_number
```
- Copy number gains/losses
```
gene_expression
```
- Over/under-expression data

python

undefined

获取拷贝数改变和基因表达数据。

可用数据类型：

```
copy_number
```
- 拷贝数增益/缺失数据
```
gene_expression
```
- 基因过表达/低表达数据

python

undefined

Download copy number data

下载拷贝数数据

download_cosmic_file( email="user@email.com", password="password", filepath="GRCh38/cosmic/latest/CosmicCompleteCNA.tsv.gz" )

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download_cosmic_file( email="user@email.com", password="password", filepath="GRCh38/cosmic/latest/CosmicCompleteCNA.tsv.gz" )

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Resistance Mutations

耐药突变

Access drug resistance mutation data with clinical annotations.

python

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访问带有临床注释的耐药突变数据。

python

undefined

Download resistance mutations

下载耐药突变数据

download_cosmic_file( email="user@email.com", password="password", filepath="GRCh38/cosmic/latest/CosmicResistanceMutations.tsv.gz" )

undefined

download_cosmic_file( email="user@email.com", password="password", filepath="GRCh38/cosmic/latest/CosmicResistanceMutations.tsv.gz" )

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Working with COSMIC Data

处理COSMIC数据

Genome Assemblies

基因组组装版本

COSMIC provides data for two reference genomes:

GRCh38 (recommended, current standard)
GRCh37 (legacy, for older pipelines)

Specify the assembly in file paths:

python

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COSMIC提供两种参考基因组的数据：

GRCh38（推荐使用，当前标准版本）
GRCh37（旧版本，适用于传统分析流程）

在文件路径中指定组装版本：

python

undefined

GRCh38 (recommended)

GRCh38（推荐）

filepath="GRCh38/cosmic/latest/CosmicMutantExport.tsv.gz"

GRCh37 (legacy)

GRCh37（旧版本）

filepath="GRCh37/cosmic/latest/CosmicMutantExport.tsv.gz"

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filepath="GRCh37/cosmic/latest/CosmicMutantExport.tsv.gz"

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Versioning

版本控制

Use
```
latest
```
in file paths to always get the most recent release
COSMIC is updated quarterly (current version: v102, May 2025)
Specific versions can be used for reproducibility:
```
v102
```
,
```
v101
```
, etc.

在文件路径中使用
```
latest
```
可始终获取最新版本的数据
COSMIC每季度更新一次（当前版本：v102，2025年5月）
可指定具体版本以保证分析可复现：
```
v102
```
、
```
v101
```
等

File Formats

文件格式

TSV/CSV: Tab/comma-separated, gzip compressed, read with pandas
VCF: Standard variant format, use with pysam, bcftools, or GATK
All files include headers describing column contents

TSV/CSV：制表符/逗号分隔的压缩文件，可使用pandas读取
VCF：标准变异格式，可与pysam、bcftools或GATK配合使用
所有文件均包含表头，用于说明各列内容

Common Analysis Patterns

常见分析模式

Filter mutations by gene:

python

import pandas as pd

mutations = pd.read_csv('cosmic_mutations.tsv.gz', sep='\t', compression='gzip')
tp53_mutations = mutations[mutations['Gene name'] == 'TP53']

Identify cancer genes by role:

python

gene_census = pd.read_csv('cancer_gene_census.csv')
oncogenes = gene_census[gene_census['Role in Cancer'].str.contains('oncogene', na=False)]
tumor_suppressors = gene_census[gene_census['Role in Cancer'].str.contains('TSG', na=False)]

Extract mutations by cancer type:

python

mutations = pd.read_csv('cosmic_mutations.tsv.gz', sep='\t', compression='gzip')
lung_mutations = mutations[mutations['Primary site'] == 'lung']

Work with VCF files:

python

import pysam

vcf = pysam.VariantFile('CosmicCodingMuts.vcf.gz')
for record in vcf.fetch('17', 7577000, 7579000):  # TP53 region
    print(record.id, record.ref, record.alts, record.info)

按基因筛选突变：

python

import pandas as pd

mutations = pd.read_csv('cosmic_mutations.tsv.gz', sep='\t', compression='gzip')
tp53_mutations = mutations[mutations['Gene name'] == 'TP53']

按基因作用类型识别癌症基因：

python

gene_census = pd.read_csv('cancer_gene_census.csv')
oncogenes = gene_census[gene_census['Role in Cancer'].str.contains('oncogene', na=False)]
tumor_suppressors = gene_census[gene_census['Role in Cancer'].str.contains('TSG', na=False)]

按癌症类型提取突变：

python

mutations = pd.read_csv('cosmic_mutations.tsv.gz', sep='\t', compression='gzip')
lung_mutations = mutations[mutations['Primary site'] == 'lung']

处理VCF文件：

python

import pysam

vcf = pysam.VariantFile('CosmicCodingMuts.vcf.gz')
for record in vcf.fetch('17', 7577000, 7579000):  # TP53区域
    print(record.id, record.ref, record.alts, record.info)

Data Reference

数据参考文档

For comprehensive information about COSMIC data structure, available files, and field descriptions, see

references/cosmic_data_reference.md

. This reference includes:

Complete list of available data types and files
Detailed field descriptions for each file type
File format specifications
Common file paths and naming conventions
Data update schedule and versioning
Citation information

Use this reference when:

Exploring what data is available in COSMIC
Understanding specific field meanings
Determining the correct file path for a data type
Planning analysis workflows with COSMIC data

如需了解COSMIC数据结构、可用文件及字段说明的全面信息，请查看

references/cosmic_data_reference.md

。该参考文档包含：

所有可用数据类型和文件的完整列表
每种文件类型的详细字段说明
文件格式规范
常见文件路径和命名规则
数据更新计划和版本控制说明
引用信息

在以下场景中可使用该参考文档：

探索COSMIC中的可用数据
理解特定字段的含义
确定对应数据类型的正确文件路径
规划基于COSMIC数据的分析流程

Helper Functions

辅助函数

The download script includes helper functions for common operations:

下载脚本包含用于常见操作的辅助函数：

Get Common File Paths

获取常用文件路径

python

from scripts.download_cosmic import get_common_file_path

python

from scripts.download_cosmic import get_common_file_path

Get path for mutations file

获取突变数据文件路径

path = get_common_file_path('mutations', genome_assembly='GRCh38')

Returns: 'GRCh38/cosmic/latest/CosmicMutantExport.tsv.gz'

返回值: 'GRCh38/cosmic/latest/CosmicMutantExport.tsv.gz'

Get path for gene census

获取癌症基因普查数据文件路径

path = get_common_file_path('gene_census')

Returns: 'GRCh38/cosmic/latest/cancer_gene_census.csv'

返回值: 'GRCh38/cosmic/latest/cancer_gene_census.csv'


**Available shortcuts**:
- `mutations` - Core coding mutations
- `mutations_vcf` - VCF format mutations
- `gene_census` - Cancer Gene Census
- `resistance_mutations` - Drug resistance data
- `structural_variants` - Structural variants
- `gene_expression` - Expression data
- `copy_number` - Copy number alterations
- `fusion_genes` - Gene fusions
- `signatures` - Mutational signatures
- `sample_info` - Sample metadata


**可用快捷方式**：
- `mutations` - 核心编码区突变
- `mutations_vcf` - VCF格式突变数据
- `gene_census` - 癌症基因普查
- `resistance_mutations` - 耐药突变数据
- `structural_variants` - 结构变异
- `gene_expression` - 表达数据
- `copy_number` - 拷贝数改变
- `fusion_genes` - 融合基因
- `signatures` - 突变特征
- `sample_info` - 样本元数据

Troubleshooting

故障排除

Authentication Errors

身份验证错误

Verify email and password are correct
Ensure account is registered at cancer.sanger.ac.uk/cosmic
Check if commercial license is required for your use case

确认邮箱和密码正确
确保账户已在cancer.sanger.ac.uk/cosmic完成注册
检查你的使用场景是否需要商业授权许可

File Not Found

文件未找到

Verify the filepath is correct
Check that the requested version exists
Use
```
latest
```
for the most recent version
Confirm genome assembly (GRCh37 vs GRCh38) is correct

确认文件路径正确
检查请求的版本是否存在
使用
```
latest
```
获取最新版本数据
确认基因组组装版本（GRCh37 vs GRCh38）正确

Large File Downloads

大文件下载

COSMIC files can be several GB in size
Ensure sufficient disk space
Download may take several minutes depending on connection
The script shows download progress for large files

COSMIC文件大小可达数GB
确保有足够的磁盘空间
下载时间可能因网络情况需要数分钟
脚本会显示大文件的下载进度

Commercial Use

商业使用

Commercial users must license COSMIC through QIAGEN
Contact: cosmic-translation@sanger.ac.uk
Academic access is free but requires registration

商业用户必须通过QIAGEN获取COSMIC授权许可
联系方式：cosmic-translation@sanger.ac.uk
学术用户可免费访问，但需要注册

Integration with Other Tools

与其他工具的集成

COSMIC data integrates well with:

Variant annotation: VEP, ANNOVAR, SnpEff
Signature analysis: SigProfiler, deconstructSigs, MuSiCa
Cancer genomics: cBioPortal, OncoKB, CIViC
Bioinformatics: Bioconductor, TCGA analysis tools
Data science: pandas, scikit-learn, PyTorch

COSMIC数据可与以下工具良好集成：

变异注释：VEP、ANNOVAR、SnpEff
特征分析：SigProfiler、deconstructSigs、MuSiCa
癌症基因组学：cBioPortal、OncoKB、CIViC
生物信息学：Bioconductor、TCGA分析工具
数据科学：pandas、scikit-learn、PyTorch

Additional Resources

其他资源

COSMIC Website: https://cancer.sanger.ac.uk/cosmic
Documentation: https://cancer.sanger.ac.uk/cosmic/help
Release Notes: https://cancer.sanger.ac.uk/cosmic/release_notes
Contact: cosmic@sanger.ac.uk

COSMIC官网：https://cancer.sanger.ac.uk/cosmic
官方文档：https://cancer.sanger.ac.uk/cosmic/help
版本发布说明：https://cancer.sanger.ac.uk/cosmic/release_notes
联系方式：cosmic@sanger.ac.uk

Citation

引用说明

When using COSMIC data, cite: Tate JG, Bamford S, Jubb HC, et al. COSMIC: the Catalogue Of Somatic Mutations In Cancer. Nucleic Acids Research. 2019;47(D1):D941-D947.

使用COSMIC数据时，请引用： Tate JG, Bamford S, Jubb HC, et al. COSMIC: the Catalogue Of Somatic Mutations In Cancer. Nucleic Acids Research. 2019;47(D1):D941-D947.