PyMisha
Python interface for misha genomic databases. PyMisha provides full read/write access to misha track databases with C++ streaming backends for genome-scale operations. |
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Features
- 1D and 2D track support: Dense, sparse, and 2D (rectangle/point) tracks with full CRUD operations.
- C++ streaming backends: Extraction, summary, quantiles, distribution, lookup, segmentation, Wilcoxon tests, correlation, and sampling all stream through C++ for performance.
- Virtual tracks: Computed-on-the-fly track views with filtering, shifting, and 30+ aggregation functions.
- Interval operations: Union, intersection, difference, canonicalization, neighbors, annotation, normalization, random generation, and liftover.
- Sequence analysis: Extraction, k-mer counting, PWM/PSSM scoring, and Markov-chain synthesis (
gsynth). - Database management: Create, link, convert, and manage misha-compatible genomic databases.
- R misha compatibility: Reads and writes the same on-disk formats as R misha (123/145 R exports covered).
Installation
pip install pymisha
Pre-built wheels are available for Linux (x86_64) and macOS (x86_64 and arm64), Python 3.10-3.12.
To install from source (requires a C++17 compiler and numpy):
pip install -e ".[dev]"
Quick start
PyMisha ships with a built-in examples database so you can start exploring immediately -- no external data needed:
import pymisha as pm
# Option 1: one-liner to load the bundled examples database
pm.gdb_init_examples()
# Option 2: equivalent explicit form
pm.gsetroot(pm.gdb_examples_path())
# List available tracks and extract data
print(pm.gtrack_ls())
print(pm.gextract("dense_track", pm.gintervals("chr1", 0, 1000)))
To connect to your own misha database, use gsetroot:
import pymisha as pm
# Initialize the database
pm.gsetroot("/path/to/misha_db")
# Create intervals and extract data
intervals = pm.gintervals_from_strings(["chr1:0-1000", "chr1:2000-2600"])
out = pm.gextract("track1", intervals, iterator=100)
# Filter and summarize
filtered = pm.gscreen("track1 > 0.5", intervals)
stats = pm.gsummary("track1", intervals)
Thread safety
PyMisha inherits R misha's single-threaded design. Keep the following constraints in mind:
- Not thread-safe. All module-level state (
_GROOT,_UROOT,_VTRACKS,CONFIG) is process-global and unsynchronized. Do not call PyMisha from multiple threads concurrently. - One database per process. You cannot have two databases open simultaneously;
gsetroot()replaces the active database globally. CONFIGis global. Changing settings likemax_processesaffects every subsequent operation in the process.- Multiprocessing uses
fork(). The C++ backend parallelizes viafork()with shared memory (mmap) and semaphores. This is transparent to the caller but means PyMisha should not be used inside already-forked worker processes or withfork-unsafe libraries.
Examples
Using the built-in example database:
import pymisha as pm
# Quickest way to get started
pm.gdb_init_examples()
# Or equivalently, using gsetroot with the examples path
pm.gsetroot(pm.gdb_examples_path())
print(pm.gtrack_ls())
print(pm.gextract("dense_track", pm.gintervals("chr1", 0, 1000)))
Creating a genome database
PyMisha ships prebuilt genome databases for common assemblies. Download and set up with a single call:
import pymisha as pm
# Download a prebuilt genome (mm9, mm10, mm39, hg19, hg38)
pm.gdb_create_genome("hg38", path="/data/genomes") # creates /data/genomes/hg38/
pm.gsetroot("/data/genomes/hg38")
pm.gchrom_sizes() # verify it worked
To build a database from your own FASTA files (e.g. a custom assembly):
pm.gdb_create("/data/my_genome", "genome.fa.gz", verbose=True)
pm.gsetroot("/data/my_genome")
See the Creating Genome Databases tutorial for UCSC download workflows and advanced options.
Optional dependencies
pyBigWig: For BigWig import ingtrack_import.pyreadr+Rscript: For loading R-serialized big interval sets.PyYAML: For richergdataset_infometadata parsing.
Using pymisha with an LLM agent
LLM coding agents (Claude Code, Copilot, Cursor) writing pymisha analysis code can pre-load these reference docs into context for fewer hallucinated APIs and more idiomatic recipes:
- agent-guides/pymisha-core.md — concepts, chooser tables, everyday recipes.
- agent-guides/pymisha-advanced.md — 2D/Hi-C, PWM, import/export, new genomes, gsynth.
- agent-guides/pymisha-anti-patterns.md — silent footguns cross-referenced from the above.
- agent-guides/skills/importing-tracks/SKILL.md — full track-import reference.
Drop-in prompt (no clone needed). Paste the block below into your agent at the start of a pymisha task. It points the agent at the raw files on GitHub, so it works without a local checkout:
Before writing any pymisha code, fetch and read:
- https://raw.githubusercontent.com/tanaylab/pymisha/main/agent-guides/pymisha-core.md (mandatory: concepts + everyday recipes)
- https://raw.githubusercontent.com/tanaylab/pymisha/main/agent-guides/pymisha-anti-patterns.md (silent footguns; cross-referenced from core)
- https://raw.githubusercontent.com/tanaylab/pymisha/main/agent-guides/pymisha-advanced.md (consult on demand: 2D/Hi-C, PWM, import/export, new genomes)
Follow the conventions in those files. When you hit a recipe with an
"Avoid:" block, treat it as a hard rule.
Pin to a release tag for stability by replacing main with any tag that contains agent-guides/. The skills/importing-tracks/SKILL.md guide listed above is load-on-demand; pull it in only when the task specifically calls for track import.
The guides mirror the equivalent set in R misha — same section numbering, same recipes, translated to the pymisha API.
Missing features
Compared to R misha, the following are not yet implemented:
- Track Arrays:
gtrack.array.*andgvtrack.array.slice. - Legacy Conversion:
gtrack.convert(for migrating old 2D formats).
License
MIT. See LICENSE for details.
1 maintainer
Release files for pymisha 0.9.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pymisha-0.9.1.tar.gz | 1.6 MB | Details |
Built distributions (wheels)
| File | Reset | |||
|---|---|---|---|---|
| pymisha-0.9.1-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl | CPython 3.12 | CPython 3.12 | Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64 | Details |
| pymisha-0.9.1-cp312-cp312-macosx_11_0_arm64.whl | CPython 3.12 | CPython 3.12 | macOS 11.0+ ARM64 | Details |
| pymisha-0.9.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl | CPython 3.11 | CPython 3.11 | Linux glibc 2.27+ x86-64, Linux glibc 2.28+ x86-64 | Details |
| pymisha-0.9.1-cp311-cp311-macosx_11_0_arm64.whl | CPython 3.11 | CPython 3.11 | macOS 11.0+ ARM64 | Details |
| pymisha-0.9.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl | CPython 3.10 | CPython 3.10 | Linux glibc 2.27+ x86-64, Linux glibc 2.28+ x86-64 | Details |
Total release size: 40.6 MB
Release files / pymisha-0.9.1.tar.gz
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