pysam
Work with genomic sequencing files
Also available from: davila7
Process and analyze DNA sequencing data with tools for reading BAM, VCF, and FASTQ files. Extract genomic regions, calculate coverage statistics, and integrate multiple file types for comprehensive variant analysis.
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Using "pysam". Open a BAM file and show coverage statistics for chromosome 1
Expected outcome:
- Chromosome 1 statistics:
- Total reads: 1,245,678
- Mapped reads: 1,198,432 (96.2%)
- Mean coverage: 32.4x
- Regions below 10x coverage: 5,234 positions
Using "pysam". Filter variants by quality and depth
Expected outcome:
- Filtered 12,456 variants to 3,892 high-quality variants
- Applied filters: QUAL > 30, DP > 10, MQ > 40
- Variants written to filtered.vcf
Using "pysam". Extract sequences around variant positions
Expected outcome:
- Extracted 100bp sequences for 847 variants
- Sequences written to variant_contexts.fasta
- Flanking region: +/- 50bp from each variant position
Security Audit
SafeAll 447 static findings are FALSE POSITIVES caused by bioinformatics terminology being misinterpreted as security-relevant patterns. The scanner flags 'SAM' as Windows Security Account Manager when it means Sequence Alignment/Map format, and samtools/bcftools as network scanning tools when they are legitimate bioinformatics command-line utilities. The skill contains only documentation and code examples for legitimate genomic data processing. No actual malicious code, command injection, credential access, or network exfiltration patterns exist.
Risk Factors
⚙️ External commands (3)
📁 Filesystem access (2)
Quality Score
What You Can Build
Variant analysis workflow
Extract and filter genetic variants from VCF files, annotate with read coverage from BAM files
Coverage analysis
Calculate per-base coverage, identify low-coverage regions, generate coverage tracks for visualization
Quality control pipeline
Validate sequencing data, check reference consistency, filter reads by quality thresholds
Try These Prompts
Use pysam to open example.bam and print all reads overlapping chr1 positions 1000-2000
Open variants.vcf and print all variants on chr2 with quality score above 30
Calculate per-base coverage for chromosome 1 positions 100000-200000 using pileup analysis
Open reference.fasta and extract the sequence for gene ABC on chr5 from position 10000 to 11000
Best Practices
- Always use indexed BAM files for random access operations to improve performance
- Remember pysam uses 0-based coordinates while VCF files use 1-based coordinates
- Use pileup() for column-wise coverage analysis instead of repeated fetch() calls
Avoid
- Loading entire BAM files into memory instead of using iterator-based processing
- Ignoring coordinate system differences between pysam and VCF file formats
- Processing large files without creating index files for random access