Install
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About
Use cases: testing, data, writing
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What's inside
- Skill name
pysam- Description
- Provides Python/HTSlib workflows for genomic files. Used when reading, querying, filtering, or writing SAM/BAM/CRAM, VCF/BCF, FASTA/FASTQ, or tabix data with pysam, including pileup, coverage, indexing, and CRAM references.
- License
- MIT
- Compatibility
- Requires Python 3.9+ and pysam 0.24.1. Bundled scripts use local files. CRAM decoding may require the matching reference FASTA or an explicitly configured REF_PATH/REF_CACHE.
- Allowed tools
- Read, Write, Edit, Bash
- Metadata
- version: 2.3 · skill-author: K-Dense Inc. · last-reviewed: 2026-10-01
- Instructions
- 355 lines in SKILL.md · view on GitHub
Before installing
- Pre-approves any shell command
- Instructions call the network
Agent Skills spec issues
- files: referenced but missing: references/sources.md, scripts/inspect_hts.py, scripts/alignment_qc.py, scripts/variant_summary.py, scripts/filter_alignments.py
Files (1)
- SKILL.md
SKILL.md (first lines)
# pysam
## Overview
Use pysam for low-level, streaming access to HTSlib-supported genomic formats:
- `AlignmentFile` and `AlignedSegment` for SAM/BAM/CRAM
- `VariantFile`, `VariantHeader`, and `VariantRecord` for VCF/BCF
- `FastaFile` for indexed FASTA and `FastxFile` for sequential FASTA/FASTQ
- `TabixFile` for BGZF-compressed, tabix-indexed BED/GFF/GTF/custom tables
- `pysam.samtools` and `pysam.bcftools` for wrapped command dispatchers
Current upstream baseline: **pysam 0.24.1** (7 September 2026), wrapping
HTSlib/samtools/bcftools 1.24. Read `references/sources.md` before updating
version-specific guidance.
## Installation
Use the pinned release for reproducible work:
```bash
uv pip install "pysam==0.24.1"
```
Confirm the runtime:
```python
import pysam
print(pysam.__version__) # 0.24.1
print(pysam.__samtools_version__) # 1.24
```
Prebuilt wheels are available for supported macOS and Linux platforms. A
source build needs a C compiler and HTSlib build dependencies; read the
official installation guide linked from `references/sources.md`.
## First Decide
Before writing code:
1. Identify the real format, compression, sort order, and available index.
2. Decide whether coordinates are numeric Python coordinates or a region
string. Do not mix them.
3. For CRAM, identify the exact reference assembly and FASTA.
4. Prefer indexed region access; use sequential iteration only when intended.
5. Preserve headers when writing and write to a new path by default.
6. State filtering semantics: mapping/base quality, flags, overlap handling,
duplicate handling, and pileup depth cap.
For unfamiliar files, start with the bundled read-only inspector:
```bash
python scripts/inspect_hts.py sample.bam
python scripts/inspect_hts.py cohort.vcf.gz
python scripts/inspect_hts.py reference.fa
```
## Bundled Scripts
| Script | Purpose | Typical call |
|---|---|---|
| `scripts/inspect_hts.py` | Metadata-only inspection for alignment, variant, FASTA, FASTQ, and tabix files | `python scripts/inspect_hts.py sample.cram --reference ref.fa` |
| `scripts/alignment_qc.py` | Streaming aggregate read/QC counts as JSON | `python scripts/alignment_qc.py sample.bam --max-records 100000` |
| `scripts/variant_summary.py` | Streaming variant, FILTER, and genotype summary as JSON | `python scripts/variant_summary.py cohort.vcf.gz --region chr1:1-1000000` |
| `scripts/filter_alignments.py` | Filter SAM/BAM/CRAM without changing record order | `python scripts/filter_alignments.py input.bam output.bam --exclude-secondary` |
All scripts refuse to overwrite existing outputs. The filter also refuses stale
output indexes and offers `--index --csi` for large BAM contigs. FASTA inspection
requires an existing `.fai`; create it explicitly with `pysam.faidx()` first.
Run each with `--help` for coordinate, index, and privacy notes.
Examples use illustrative filenames and assay-specific thresholds. The local
synthetic suite exercises these API patterns on pysam 0.24.1; remote storage and
biological datasets are not part of that validation.
## Coordinate Contract
**Numeric coordinates accepted by pysam APIs are 0-based, half-open.** This
includes numeric `AlignmentFile.fetch()`, `VariantFile.fetch()`,
`FastaFile.fetch()`, `TabixFile.fetch()`, and `pileup()` arguments.
**Region strings are samtools-style: 1-based and inclusive.**
```python
# The same 100 bases:
bam.fetch("chr1", 99, 199) # [99, 199)
bam.fetch(region="chr1:100-199") # 1-based inclusive
```
VCF text uses 1-based `POS`, while record properties expose both systems:
```python
record.pos # 1-based
record.start # 0-based inclusive
record.stop # 0-based exclusive
```
Read `references/coordinates_and_indexing.md` for format conversions, overlap
semantics, index choices, and contig-name checks.
## Alignment Files
Use context managers and explicit modes:
```python
import pysam
with pysam.AlignmentFile("sample.bam", "rb", threads=4) as bam:
for read in bam.fetch("chr1", 1_000, 2_000):
if (
not read.is_unmapped
and not read.is_secondary
and not read.is_supplementary
and read.mapping_quality >= 30
):
print(read.query_name, read.reference_start, read.cigarstring)
```From bioassembly/antigravity-sage, MIT.
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Oct 8, 2026 (21 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- Version
- 2.3
- License
- MIT
- Repository
- github.com/bioassembly/antigravity-sage
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
pysam skill. Agent Mart. https://agentmart.dev/skills/bioassembly-pysam (last updated 2026-10-24)