ClinVar数据库使用指南：基因变异临床意义查询、API访问与数据分析

clinvar-database by davila7/claude-code-templates

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安装命令

npx skills add https://github.com/davila7/claude-code-templates --skill clinvar-database

科研工具生物信息学数据处理

🇨🇳中文介绍

ClinVar 数据库

概述

ClinVar 是美国国家生物技术信息中心（NCBI）维护的一个免费访问的数据库，用于存档人类遗传变异与表型之间关系的报告及其支持性证据。该数据库汇总了基因组变异及其与人类健康关系的信息，提供了临床遗传学和研究中使用的标准化变异分类。

何时使用此技能

在以下情况下应使用此技能：

通过基因、疾病或临床意义搜索变异
解读临床意义分类（致病性、良性、意义未明）
通过 E-utilities API 以编程方式访问 ClinVar 数据
从 FTP 下载和处理批量数据
理解审阅状态和星级评级
解决相互矛盾的变异解读
用临床意义注释变异调用集

核心功能

1. 搜索和查询 ClinVar

网页界面查询

通过网页界面在 https://www.ncbi.nlm.nih.gov/clinvar/ 搜索 ClinVar

常用搜索模式：

按基因：BRCA1[gene]
按临床意义：pathogenic[CLNSIG]
按疾病：breast cancer[disorder]
按变异：NM_000059.3:c.1310_1313del[variant name]

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2. 解读临床意义

ClinVar 使用标准化的术语进行变异分类。请参阅 references/clinical_significance.md 获取详细的解读指南。

关键种系分类术语（ACMG/AMP）：

致病性 - 变异导致疾病（约 99% 概率）
可能致病性 - 变异很可能导致疾病（约 90% 概率）
意义未明 - 证据不足以进行分类
可能良性 - 变异很可能不导致疾病
良性 - 变异不导致疾病

审阅状态（星级评级）：

★★★★ 实践指南 - 置信度最高
★★★ 专家小组审阅（例如，ClinGen）- 高置信度
★★ 多个提交者，无冲突 - 中等置信度
★ 单个提交者，有标准 - 标准权重
☆ 无断言标准 - 低置信度

关键注意事项：

始终检查审阅状态 - 优先选择 ★★★ 或 ★★★★ 评级
相互矛盾的解读需要人工评估
随着新证据的出现，分类可能会改变
VUS（意义未明）变异缺乏足够的证据用于临床

3. 从 FTP 下载批量数据

访问 ClinVar FTP 站点

从 ftp://ftp.ncbi.nlm.nih.gov/pub/clinvar/ 下载完整的数据集

请参阅 references/data_formats.md 获取关于文件格式和处理的全面文档。

月度发布：每月第一个星期四（完整数据集，已归档）
每周更新：每周一（增量更新）

XML 文件（最全面）：

VCV（变异）文件：xml/clinvar_variation/ - 以变异为中心的聚合
RCV（记录）文件：xml/RCV/ - 变异-疾病对
包含完整的提交详情、证据和元数据

VCF 文件（用于基因组流程）：

GRCh37：vcf_GRCh37/clinvar.vcf.gz
GRCh38：vcf_GRCh38/clinvar.vcf.gz
限制：排除 >10kb 的变异和复杂的结构变异

制表符分隔文件（用于快速分析）：

tab_delimited/variant_summary.txt.gz - 所有变异的摘要
tab_delimited/var_citations.txt.gz - PubMed 引用
tab_delimited/cross_references.txt.gz - 数据库交叉引用

# 下载最新的月度 XML 发布版本
wget ftp://ftp.ncbi.nlm.nih.gov/pub/clinvar/xml/clinvar_variation/ClinVarVariationRelease_00-latest.xml.gz

# 下载 GRCh38 的 VCF 文件
wget ftp://ftp.ncbi.nlm.nih.gov/pub/clinvar/vcf_GRCh38/clinvar.vcf.gz

4. 处理和分析 ClinVar 数据

处理 XML 文件以提取变异详情、分类和证据。

使用 xml.etree 的 Python 示例：

import gzip
import xml.etree.ElementTree as ET

with gzip.open('ClinVarVariationRelease.xml.gz', 'rt') as f:
    for event, elem in ET.iterparse(f, events=('end',)):
        if elem.tag == 'VariationArchive':
            variation_id = elem.attrib.get('VariationID')
            # 提取临床意义、审阅状态等
            elem.clear()  # 释放内存

使用 bcftools 或 Python 注释变异调用或按临床意义过滤。

使用 bcftools：

# 过滤致病性变异
bcftools view -i 'INFO/CLNSIG~"Pathogenic"' clinvar.vcf.gz

# 提取特定基因
bcftools view -i 'INFO/GENEINFO~"BRCA"' clinvar.vcf.gz

# 用 ClinVar 注释你的 VCF
bcftools annotate -a clinvar.vcf.gz -c INFO your_variants.vcf

在 Python 中使用 PyVCF：

import vcf

vcf_reader = vcf.Reader(filename='clinvar.vcf.gz')
for record in vcf_reader:
    clnsig = record.INFO.get('CLNSIG', [])
    if 'Pathogenic' in clnsig:
        gene = record.INFO.get('GENEINFO', [''])[0]
        print(f"{record.CHROM}:{record.POS} {gene} - {clnsig}")

处理制表符分隔文件

使用 pandas 或命令行工具进行快速过滤和分析。

使用 pandas：

import pandas as pd

# 加载变异摘要
df = pd.read_csv('variant_summary.txt.gz', sep='\t', compression='gzip')

# 过滤特定基因中的致病性变异
pathogenic_brca = df[
    (df['GeneSymbol'] == 'BRCA1') &
    (df['ClinicalSignificance'].str.contains('Pathogenic', na=False))
]

# 按临床意义统计变异数量
sig_counts = df['ClinicalSignificance'].value_counts()

使用命令行工具：

# 提取特定基因的致病性变异
zcat variant_summary.txt.gz | \
  awk -F'\t' '$7=="TP53" && $13~"Pathogenic"' | \
  cut -f1,5,7,13,14

5. 处理相互矛盾的解读

当多个提交者对同一变异提供不同的分类时，ClinVar 会报告“致病性解读存在矛盾”。

检查审阅状态（星级评级）- 更高的评级权重更大
检查每个提交者的证据和断言标准
考虑提交日期 - 较新的提交可能反映了更新的证据
查看群体频率数据（例如，gnomAD）以获取背景信息
在可用时参考专家小组分类（★★★）
对于临床使用，始终遵从遗传学专业人士的意见

排除矛盾的搜索查询：

TP53[gene] AND pathogenic[CLNSIG] NOT conflicting[RVSTAT]

6. 跟踪分类更新

随着新证据的出现，变异分类可能会随时间改变。

分类改变的原因：

新的功能研究或临床数据
更新的群体频率信息
修订的 ACMG/AMP 指南
来自更多家庭的分离数据

记录 ClinVar 版本和访问日期以确保可重复性
定期重新检查关键变异的分类
订阅 ClinVar 邮件列表以获取重大更新
使用月度归档版本获取稳定数据集

7. 向 ClinVar 提交数据

组织可以向 ClinVar 提交变异解读。

网页提交门户：https://submit.ncbi.nlm.nih.gov/subs/clinvar/
API 提交（需要服务账户）：参见 references/api_reference.md
通过 Excel 模板批量提交

拥有 NCBI 的组织账户
断言标准（最好遵循 ACMG/AMP 指南）
支持分类的证据

联系方式：clinvar@ncbi.nlm.nih.gov 以设置提交账户。

示例 1：识别基因中高置信度的致病性变异

目标： 查找 CFTR 基因中经过专家小组审阅的致病性变异。

使用网页界面或 E-utilities 搜索：

CFTR[gene] AND pathogenic[CLNSIG] AND (reviewed by expert panel[RVSTAT] OR practice guideline[RVSTAT])

查看结果，注意审阅状态（应为 ★★★ 或 ★★★★）
导出变异列表或通过 efetch 检索完整记录
如果适用，与临床表现进行交叉参考

示例 2：用 ClinVar 分类注释 VCF

目标： 向变异调用添加临床意义注释。

下载相应的 ClinVar VCF（匹配基因组版本：GRCh37 或 GRCh38）：

wget ftp://ftp.ncbi.nlm.nih.gov/pub/clinvar/vcf_GRCh38/clinvar.vcf.gz
wget ftp://ftp.ncbi.nlm.nih.gov/pub/clinvar/vcf_GRCh38/clinvar.vcf.gz.tbi

使用 bcftools 进行注释：

bcftools annotate -a clinvar.vcf.gz \
  -c INFO/CLNSIG,INFO/CLNDN,INFO/CLNREVSTAT \
  -o annotated_variants.vcf \
  your_variants.vcf

过滤已注释的 VCF 以获取致病性变异：

bcftools view -i 'INFO/CLNSIG~"Pathogenic"' annotated_variants.vcf

示例 3：分析特定疾病相关的变异

目标： 研究与遗传性乳腺癌相关的所有变异。

按疾病搜索：

hereditary breast cancer[disorder] OR "Breast-ovarian cancer, familial"[disorder]

将结果下载为 CSV 或通过 E-utilities 检索
按审阅状态过滤以优先处理高置信度变异
分析跨基因（BRCA1、BRCA2、PALB2 等）的分布
单独检查存在矛盾解读的变异

示例 4：批量下载和数据库构建

目标： 为分析流程构建本地 ClinVar 数据库。

下载月度发布版本以确保可重复性：

wget ftp://ftp.ncbi.nlm.nih.gov/pub/clinvar/xml/clinvar_variation/ClinVarVariationRelease_YYYY-MM.xml.gz

解析 XML 并加载到数据库（PostgreSQL、MySQL、MongoDB）
按基因、位置、临床意义、审阅状态建立索引
为更新实施版本跟踪
从 FTP 站点安排月度更新

重要限制和注意事项

并非所有提交都具有同等权重 - 检查审阅状态（星级评级）
存在相互矛盾的解读 - 需要人工评估
历史提交可能已过时 - 较新的数据可能更准确
VUS 分类不是临床诊断 - 意味着证据不足

不用于直接临床诊断 - 始终需要遗传学专业人士参与
具有群体特异性 - 变异频率因血统而异
覆盖不完整 - 并非所有基因或变异都得到了充分研究
版本依赖性 - 在整个分析中协调基因组版本（GRCh37/GRCh38）

VCF 文件排除大变异 - >10kb 的变异不在 VCF 格式中
API 速率限制 - 无密钥时 3 次/秒，有 API 密钥时 10 次/秒
文件大小 - 完整的 XML 发布版本是多 GB 的压缩文件
无实时更新 - 网站每周更新，FTP 每月/每周更新

此技能包含全面的参考文档：

references/api_reference.md - 完整的 E-utilities API 文档，包含 esearch、esummary、efetch 和 elink 的示例；包括速率限制、身份验证以及 Python/Biopython 代码示例
references/clinical_significance.md - 解读临床意义分类、审阅状态星级评级、冲突解决和变异解读最佳实践的详细指南
references/data_formats.md - XML、VCF 和制表符分隔文件格式的文档；FTP 目录结构、处理示例和格式选择指南

ClinVar 主页：https://www.ncbi.nlm.nih.gov/clinvar/
ClinVar 文档：https://www.ncbi.nlm.nih.gov/clinvar/docs/
E-utilities 文档：https://www.ncbi.nlm.nih.gov/books/NBK25501/
ACMG 变异解读指南：Richards 等人，2015 年（PMID：25741868）
ClinGen 专家小组：https://clinicalgenome.org/

有关 ClinVar 或数据提交的问题：clinvar@ncbi.nlm.nih.gov

🇺🇸English

ClinVar Database

Overview

ClinVar is NCBI's freely accessible archive of reports on relationships between human genetic variants and phenotypes, with supporting evidence. The database aggregates information about genomic variation and its relationship to human health, providing standardized variant classifications used in clinical genetics and research.

When to Use This Skill

This skill should be used when:

Searching for variants by gene, condition, or clinical significance
Interpreting clinical significance classifications (pathogenic, benign, VUS)
Accessing ClinVar data programmatically via E-utilities API
Downloading and processing bulk data from FTP
Understanding review status and star ratings
Resolving conflicting variant interpretations
Annotating variant call sets with clinical significance

Core Capabilities

1. Search and Query ClinVar

Web Interface Queries

Search ClinVar using the web interface at https://www.ncbi.nlm.nih.gov/clinvar/

Common search patterns:

By gene: BRCA1[gene]
By clinical significance: pathogenic[CLNSIG]
By condition: breast cancer[disorder]
By variant: NM_000059.3:c.1310_1313del[variant name]
By chromosome: 13[chr]
Combined: BRCA1[gene] AND pathogenic[CLNSIG]

Programmatic Access via E-utilities

Access ClinVar programmatically using NCBI's E-utilities API. Refer to references/api_reference.md for comprehensive API documentation including:

esearch - Search for variants matching criteria
esummary - Retrieve variant summaries
efetch - Download full XML records
elink - Find related records in other NCBI databases

Quick example using curl:

# Search for pathogenic BRCA1 variants
curl "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?db=clinvar&term=BRCA1[gene]+AND+pathogenic[CLNSIG]&retmode=json"

Best practices:

Test queries on the web interface before automating
Use API keys to increase rate limits from 3 to 10 requests/second
Implement exponential backoff for rate limit errors
Set Entrez.email when using Biopython

2. Interpret Clinical Significance

Understanding Classifications

ClinVar uses standardized terminology for variant classifications. Refer to references/clinical_significance.md for detailed interpretation guidelines.

Key germline classification terms (ACMG/AMP):

Pathogenic (P) - Variant causes disease (~99% probability)
Likely Pathogenic (LP) - Variant likely causes disease (~90% probability)
Uncertain Significance (VUS) - Insufficient evidence to classify
Likely Benign (LB) - Variant likely does not cause disease
Benign (B) - Variant does not cause disease

Review status (star ratings):

★★★★ Practice guideline - Highest confidence
★★★ Expert panel review (e.g., ClinGen) - High confidence
★★ Multiple submitters, no conflicts - Moderate confidence
★ Single submitter with criteria - Standard weight
☆ No assertion criteria - Low confidence

Critical considerations:

Always check review status - prefer ★★★ or ★★★★ ratings
Conflicting interpretations require manual evaluation
Classifications may change as new evidence emerges
VUS (uncertain significance) variants lack sufficient evidence for clinical use

3. Download Bulk Data from FTP

Access ClinVar FTP Site

Download complete datasets from ftp://ftp.ncbi.nlm.nih.gov/pub/clinvar/

Refer to references/data_formats.md for comprehensive documentation on file formats and processing.

Update schedule:

Monthly releases: First Thursday of each month (complete dataset, archived)
Weekly updates: Every Monday (incremental updates)

Available Formats

XML files (most comprehensive):

VCV (Variation) files: xml/clinvar_variation/ - Variant-centric aggregation
RCV (Record) files: xml/RCV/ - Variant-condition pairs
Include full submission details, evidence, and metadata

VCF files (for genomic pipelines):

GRCh37: vcf_GRCh37/clinvar.vcf.gz
GRCh38: vcf_GRCh38/clinvar.vcf.gz
Limitations: Excludes variants >10kb and complex structural variants

Tab-delimited files (for quick analysis):

tab_delimited/variant_summary.txt.gz - Summary of all variants
tab_delimited/var_citations.txt.gz - PubMed citations
tab_delimited/cross_references.txt.gz - Database cross-references

Example download:

# Download latest monthly XML release
wget ftp://ftp.ncbi.nlm.nih.gov/pub/clinvar/xml/clinvar_variation/ClinVarVariationRelease_00-latest.xml.gz

# Download VCF for GRCh38
wget ftp://ftp.ncbi.nlm.nih.gov/pub/clinvar/vcf_GRCh38/clinvar.vcf.gz

4. Process and Analyze ClinVar Data

Working with XML Files

Process XML files to extract variant details, classifications, and evidence.

Python example with xml.etree:

import gzip
import xml.etree.ElementTree as ET

with gzip.open('ClinVarVariationRelease.xml.gz', 'rt') as f:
    for event, elem in ET.iterparse(f, events=('end',)):
        if elem.tag == 'VariationArchive':
            variation_id = elem.attrib.get('VariationID')
            # Extract clinical significance, review status, etc.
            elem.clear()  # Free memory

Working with VCF Files

Annotate variant calls or filter by clinical significance using bcftools or Python.

Using bcftools:

# Filter pathogenic variants
bcftools view -i 'INFO/CLNSIG~"Pathogenic"' clinvar.vcf.gz

# Extract specific genes
bcftools view -i 'INFO/GENEINFO~"BRCA"' clinvar.vcf.gz

# Annotate your VCF with ClinVar
bcftools annotate -a clinvar.vcf.gz -c INFO your_variants.vcf

Using PyVCF in Python:

import vcf

vcf_reader = vcf.Reader(filename='clinvar.vcf.gz')
for record in vcf_reader:
    clnsig = record.INFO.get('CLNSIG', [])
    if 'Pathogenic' in clnsig:
        gene = record.INFO.get('GENEINFO', [''])[0]
        print(f"{record.CHROM}:{record.POS} {gene} - {clnsig}")

Working with Tab-Delimited Files

Use pandas or command-line tools for rapid filtering and analysis.

Using pandas:

import pandas as pd

# Load variant summary
df = pd.read_csv('variant_summary.txt.gz', sep='\t', compression='gzip')

# Filter pathogenic variants in specific gene
pathogenic_brca = df[
    (df['GeneSymbol'] == 'BRCA1') &
    (df['ClinicalSignificance'].str.contains('Pathogenic', na=False))
]

# Count variants by clinical significance
sig_counts = df['ClinicalSignificance'].value_counts()

Using command-line tools:

# Extract pathogenic variants for specific gene
zcat variant_summary.txt.gz | \
  awk -F'\t' '$7=="TP53" && $13~"Pathogenic"' | \
  cut -f1,5,7,13,14

5. Handle Conflicting Interpretations

When multiple submitters provide different classifications for the same variant, ClinVar reports "Conflicting interpretations of pathogenicity."

Resolution strategy:

Check review status (star rating) - higher ratings carry more weight
Examine evidence and assertion criteria from each submitter
Consider submission dates - newer submissions may reflect updated evidence
Review population frequency data (e.g., gnomAD) for context
Consult expert panel classifications (★★★) when available
For clinical use, always defer to a genetics professional

Search query to exclude conflicts:

TP53[gene] AND pathogenic[CLNSIG] NOT conflicting[RVSTAT]

6. Track Classification Updates

Variant classifications may change over time as new evidence emerges.

Why classifications change:

New functional studies or clinical data
Updated population frequency information
Revised ACMG/AMP guidelines
Segregation data from additional families

Best practices:

Document ClinVar version and access date for reproducibility
Re-check classifications periodically for critical variants
Subscribe to ClinVar mailing list for major updates
Use monthly archived releases for stable datasets

7. Submit Data to ClinVar

Organizations can submit variant interpretations to ClinVar.

Submission methods:

Web submission portal: https://submit.ncbi.nlm.nih.gov/subs/clinvar/
API submission (requires service account): See references/api_reference.md
Batch submission via Excel templates

Requirements:

Organizational account with NCBI
Assertion criteria (preferably ACMG/AMP guidelines)
Supporting evidence for classification

Contact: clinvar@ncbi.nlm.nih.gov for submission account setup.

Workflow Examples

Example 1: Identify High-Confidence Pathogenic Variants in a Gene

Objective: Find pathogenic variants in CFTR gene with expert panel review.

Steps:

Search using web interface or E-utilities:

CFTR[gene] AND pathogenic[CLNSIG] AND (reviewed by expert panel[RVSTAT] OR practice guideline[RVSTAT])

Review results, noting review status (should be ★★★ or ★★★★)
Export variant list or retrieve full records via efetch
Cross-reference with clinical presentation if applicable

Example 2: Annotate VCF with ClinVar Classifications

Objective: Add clinical significance annotations to variant calls.

Steps:

Download appropriate ClinVar VCF (match genome build: GRCh37 or GRCh38):

wget ftp://ftp.ncbi.nlm.nih.gov/pub/clinvar/vcf_GRCh38/clinvar.vcf.gz
wget ftp://ftp.ncbi.nlm.nih.gov/pub/clinvar/vcf_GRCh38/clinvar.vcf.gz.tbi

Annotate using bcftools:

bcftools annotate -a clinvar.vcf.gz \
  -c INFO/CLNSIG,INFO/CLNDN,INFO/CLNREVSTAT \
  -o annotated_variants.vcf \
  your_variants.vcf

Filter annotated VCF for pathogenic variants:

bcftools view -i 'INFO/CLNSIG~"Pathogenic"' annotated_variants.vcf

Example 3: Analyze Variants for a Specific Disease

Objective: Study all variants associated with hereditary breast cancer.

Steps:

Search by condition:

hereditary breast cancer[disorder] OR "Breast-ovarian cancer, familial"[disorder]

Download results as CSV or retrieve via E-utilities
Filter by review status to prioritize high-confidence variants
Analyze distribution across genes (BRCA1, BRCA2, PALB2, etc.)
Examine variants with conflicting interpretations separately

Example 4: Bulk Download and Database Construction

Objective: Build a local ClinVar database for analysis pipeline.

Steps:

Download monthly release for reproducibility:

wget ftp://ftp.ncbi.nlm.nih.gov/pub/clinvar/xml/clinvar_variation/ClinVarVariationRelease_YYYY-MM.xml.gz

Parse XML and load into database (PostgreSQL, MySQL, MongoDB)
Index by gene, position, clinical significance, review status
Implement version tracking for updates
Schedule monthly updates from FTP site

Important Limitations and Considerations

Data Quality

Not all submissions have equal weight - Check review status (star ratings)
Conflicting interpretations exist - Require manual evaluation
Historical submissions may be outdated - Newer data may be more accurate
VUS classification is not a clinical diagnosis - Means insufficient evidence

Scope Limitations

Not for direct clinical diagnosis - Always involve genetics professional
Population-specific - Variant frequencies vary by ancestry
Incomplete coverage - Not all genes or variants are well-studied
Version dependencies - Coordinate genome build (GRCh37/GRCh38) across analyses

Technical Limitations

VCF files exclude large variants - Variants >10kb not in VCF format
Rate limits on API - 3 req/sec without key, 10 req/sec with API key
File sizes - Full XML releases are multi-GB compressed files
No real-time updates - Website updated weekly, FTP monthly/weekly

Resources

Reference Documentation

This skill includes comprehensive reference documentation:

references/api_reference.md - Complete E-utilities API documentation with examples for esearch, esummary, efetch, and elink; includes rate limits, authentication, and Python/Biopython code samples
references/clinical_significance.md - Detailed guide to interpreting clinical significance classifications, review status star ratings, conflict resolution, and best practices for variant interpretation
references/data_formats.md - Documentation for XML, VCF, and tab-delimited file formats; FTP directory structure, processing examples, and format selection guidance

External Resources

ClinVar home: https://www.ncbi.nlm.nih.gov/clinvar/
ClinVar documentation: https://www.ncbi.nlm.nih.gov/clinvar/docs/
E-utilities documentation: https://www.ncbi.nlm.nih.gov/books/NBK25501/
ACMG variant interpretation guidelines: Richards et al., 2015 (PMID: 25741868)
ClinGen expert panels: https://clinicalgenome.org/

Contact

For questions about ClinVar or data submission: clinvar@ncbi.nlm.nih.gov

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免费AI数据抓取智能体：自动化收集、丰富与存储网站/API数据

1,100 周安装

ClinVar数据库使用指南：基因变异临床意义查询、API访问与数据分析

🇨🇳中文介绍

ClinVar 数据库

概述

何时使用此技能

核心功能

1. 搜索和查询 ClinVar

网页界面查询

相关 Skills

通过 E-utilities 进行编程访问

2. 解读临床意义

理解分类

3. 从 FTP 下载批量数据

访问 ClinVar FTP 站点

可用格式

4. 处理和分析 ClinVar 数据

处理 XML 文件

处理 VCF 文件

处理制表符分隔文件

5. 处理相互矛盾的解读

6. 跟踪分类更新

7. 向 ClinVar 提交数据

工作流程示例

示例 1：识别基因中高置信度的致病性变异

示例 2：用 ClinVar 分类注释 VCF

示例 3：分析特定疾病相关的变异

示例 4：批量下载和数据库构建

重要限制和注意事项

数据质量

范围限制

技术限制

资源

参考文档

外部资源

联系方式

🇺🇸English

ClinVar Database

Overview

When to Use This Skill

Core Capabilities

1. Search and Query ClinVar

Web Interface Queries

Programmatic Access via E-utilities

2. Interpret Clinical Significance

Understanding Classifications

3. Download Bulk Data from FTP

Access ClinVar FTP Site

Available Formats

4. Process and Analyze ClinVar Data

Working with XML Files

Working with VCF Files

Working with Tab-Delimited Files

5. Handle Conflicting Interpretations

6. Track Classification Updates

7. Submit Data to ClinVar

Workflow Examples

Example 1: Identify High-Confidence Pathogenic Variants in a Gene

Example 2: Annotate VCF with ClinVar Classifications

Example 3: Analyze Variants for a Specific Disease

Example 4: Bulk Download and Database Construction

Important Limitations and Considerations

Data Quality

Scope Limitations

Technical Limitations

Resources

Reference Documentation

External Resources

Contact

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